Dialogue system and vehicle using the same

ABSTRACT

A dialogue system and a vehicle having the same is provided. The dialogue system may recognize the user&#39;s speech, which is transmitted from the speech input device, as a text, derive user labeling context information after verifying an entity of the text, store the user labeling context information in the type to share an entity ontology with other user, and generate a dialogue response to perform an action corresponding when a user performs a free utterance or a designated entity utterance.

CROSS-REFERENCE TO RELATED APPLICATION(S)

The present application claims priority to and the benefit of KoreanPatent Application No. 10-2018-0072107, filed on Jun. 22, 2018, which isincorporated by reference herein in its entirety.

TECHNICAL FIELD

The present disclosure relates to a dialogue system and a vehicle usingthe same.

BACKGROUND

The statement in this section merely provide background informationrelated to the present disclosure and may not constitute prior art.

As for an audio-video-navigation (AVN) device of a vehicle or mostmobile devices, when providing visual information to a user or receivinga user's input, a small screen and a small button provided therein maycause the user inconvenience.

Particularly, during the driving, when a user takes off his or her handfrom a steering wheel or when a user looks up at another place forchecking the visual information and operating devices, it may be aserious danger to the safe driving.

Therefore, when applying a dialogue system to a vehicle, it may bepossible to provide services in more convenient and safer manner,wherein the dialogue system is capable of recognizing a user's intentionthrough dialogue with the user and providing information or servicenecessary for the user.

SUMMARY

Therefore, it is an aspect of the present disclosure to provide adialogue system capable of recording a speech when context informationis uttered by a user in a vehicle, and labeling the speech, and thenproviding the labeling information by recognizing a context in thevehicle so that the user uses the labeling information as reference datato perform an appropriate action, and a vehicle using the same.

Additional aspects of the present disclosure will be set forth in partin the description which follows and, in part, will be obvious from thedescription, or may be learned by practice of the present disclosure.

In accordance with an aspect of the disclosure, a dialogue systemincludes an input processor configured to: recognize a user's speech asa text; assign a weight to the text based on objective contextinformation when the user's speech is recognized; derive user labelingcontext information after verifying an entity of the text; and when afree utterance of the user or a designated entity utterance of the useroccurs, acquire at least one of an action or a pre-utterance messagecomprising an utterance content to be output, wherein the actioncorresponds to the free utterance of the user or the designated entityutterance of the user; a storage configured to: store the user labelingcontext information; and manage the user labeling context information ina form that allows an entity ontology to be shared with other user; adialogue manager, when the input processor acquires the action,configured to acquire an action parameter value that is used to performthe action from the storage; and a result processor, when the inputprocessor acquires the action, configured to generate a dialogueresponse to perform the action by using the action parameter value.

The input processor may be configured to perform morphological analysison the user's speech corresponding to a language; and convert the user'sspeech into the text.

The input processor may be configured to correct the text using a uniquenamed entity recognition when a pre-stored unique named entity includinga place, a name, a music, and a movie is stored in the storage.

The input processor may be configured to call objective contextinformation including at least one of time information, placeinformation, schedule, user's position in inside or outside of thevehicle or driving information from the storage; and assign the weightaccording to an importance and a specificity of the objective contextinformation.

The input processor may be configured to search for an entity having ahigher weight priority; derive the user labeling context information byusing a word that describes a characteristics of the entity, as a label;and transmit the user labeling context information to the storage forconstituting ontology.

The input processor may be configured to search for the entity includedin a pre-stored ontology in the storage; derive the user labelingcontext information by using the word that describes the characteristicsof the entity, as the label; and transmit the user labeling contextinformation to the storage for constituting ontology.

The input processor may be configured to derive the user labelingcontext information by referring to pre-stored user information.

The pre-stored user information may include at least one of personalinformation, family, schedule, telephone number, preference,personality, educational history, occupation, current position, previousposition or previous dialogue contents.

When storing the user labeling context information, the storage may beconfigured to store a labeling result and a frequency of referencing theentity ontology by searching for a corresponding entity in a pre-storedontology structure.

The storage may be configured to set and store the labeling result andthe frequency of referencing the entity ontology as one of sharing ornon-sharing based on a user setting.

When the free utterance of the user or the designated entity utteranceof the user is performed, the dialogue manager may be configured toacquire the user labeling context information corresponding to the freeutterance of the user or the designated entity utterance of the userfrom the storage.

The input processor may be configured to determine whether a new routeof the vehicle corresponds to a pre-utterance context that is identicalto the objective context information; and when it is determined that thenew route of the vehicle corresponds to the pre-utterance context,acquire entity ontology information corresponding to the objectivecontext information as the pre-utterance message from the storage.

When the input processor acquires the pre-utterance message, the resultprocessor may be configured to generate a dialogue responsecorresponding to the pre-utterance message.

The input processor may be configured to receive a user's utterance froma speech input device provided inside or outside of the vehicle when atrigger signal is generated or a button for the user's utterance isselected, wherein the trigger signal is generated when at least one of apredetermined speech or a predetermined gesture is performed by theuser.

In accordance with another aspect of the disclosure, a vehicle includesa speech input device configured to receive a user's speech and transmitthe user's speech when a trigger signal for an utterance is generated bya user; and a dialogue system configured to recognize the user's speechas a text; derive user labeling context information after verifying anentity of the text; store the user labeling context information in aform that allows an entity ontology to be shared with other user; andgenerate a dialogue response to perform a corresponding action when theuser performs a free utterance or a designated entity utterance.

The speech input device may be configured to receive the user's speechwhen the trigger signal is generated or a button for a user's utteranceis selected, wherein the trigger signal is generated when at least oneof a predetermined speech or a predetermined gesture is performed by theuser.

The dialogue system may include an input processor configured torecognize the user's speech as a text; assign a weight to the text basedon objective context information when the user's speech is recognized;derive user labeling context information after verifying an entity ofthe text; and when a free utterance of the user or a designated entityutterance of the user occurs, acquire at least one of an action or apre-utterance message including an utterance content to be output,wherein the action corresponds to the free utterance of the user or thedesignated entity utterance of the user; a storage configured to storethe user labeling context information; and manage the user labelingcontext information in a form that allows an entity ontology to beshared with other user; a dialogue manager, when the input processoracquires the action, configured to acquire an action parameter valuethat is used to perform the action from the storage; and a resultprocessor, when the input processor acquires the action, configured togenerate a dialogue response to perform the action by using the actionparameter value.

The input processor may be configured to call the objective contextinformation including at least one of time information, placeinformation, schedule, user's position in inside or outside of thevehicle or driving information from the storage; and assign the weightaccording to an importance and a specificity of the objective contextinformation.

When storing the user labeling context information, the storage may beconfigured to store a labeling result and a frequency of referencing theentity ontology by searching for a corresponding entity in a pre-storedontology structure.

When the free utterance of the user or the designated entity utteranceof the user is performed, the dialogue manager may be configured toacquire the user labeling context information corresponding to the freeutterance of the user or the designated entity utterance of the userfrom the storage.

The input processor may be configured to determine whether a new routeof the vehicle corresponds to a pre-utterance context that is identicalto the objective context information; and when it is determined that thenew route of the vehicle corresponds to the pre-utterance context,acquire entity ontology information corresponding to the objectivecontext information as the pre-utterance message from the storage.

Further areas of applicability will become apparent from the descriptionprovided herein. It should be understood that the description andspecific examples are intended for purposes of illustration only and arenot intended to limit the scope of the present disclosure.

DRAWINGS

In order that the disclosure may be well understood, there will now bedescribed various forms thereof, given by way of example, referencebeing made to the accompanying drawings, in which:

FIG. 1 is a control block diagram illustrating a dialogue system inaccordance with an embodiment of the present disclosure;

FIG. 2 is a view illustrating an interior of a vehicle;

FIGS. 3 to 5 are views illustrating an example of dialogue exchangedbetween a dialogue system and a driver;

FIGS. 6 and 7 are control block diagrams schematically illustrating aconnection between the dialogue system and components of the vehicle;

FIGS. 8 and 9 are control block diagrams schematically illustrating aconnection between components of the dialogue system and the componentsof the vehicle;

FIG. 10 is a control block diagram illustrating a vehicle independentmethod in which a dialogue system is provided in a vehicle;

FIGS. 11 and 12 are control block diagrams illustrating a vehiclegateway method in which a dialogue system is provided in a remote serverand a vehicle acts as a gateway connecting a user to the dialoguesystem;

FIG. 13 is a control block diagram illustrating a case in which thevehicle can perform some input processing and output processing in thevehicle gateway method;

FIG. 14 is a control block diagram illustrating a hybrid method in whichboth of a remote dialogue system server and a vehicle perform a dialogueprocessing;

FIGS. 15 and 16 are control block diagrams illustrating a mobile gatewaymethod in which a mobile device connected to a vehicle connects a userto a remote dialogue system server;

FIG. 17 is a control block diagram illustrating a mobile independentmethod in which a dialogue system is provided in a mobile device;

FIGS. 18, 19A and 19B are control block diagrams illustrating aconfiguration of an input processor in the configuration of the dialoguesystem in detail;

FIGS. 20A and 20B are views illustrating an example of informationstored in a context understanding table;

FIG. 21 is a control block diagram illustrating a dialogue systemapplicable to a case in which the dialogue system first outputs anutterance before receiving a user's input;

FIGS. 22A, 22B and 22C are views illustrating an example of informationstored in a pre-utterance condition table;

FIG. 23 is a control block diagram illustrating a configuration of adialogue manager in detail;

FIG. 24 is a view illustrating an example of information stored in arelational action DB;

FIG. 25 is a view illustrating an example of information stored in anaction execution condition DB;

FIG. 26 is a view illustrating an example of information stored in anaction parameter DB;

FIG. 27 is a table illustrating an example of information stored in theambiguity resolution information DB;

FIGS. 28A and 28B are tables illustrating a variety of examples in whichthe vehicle control is performed since the ambiguity solver resolves theambiguity by referring to the ambiguity resolution information DB andextracting an action;

FIG. 29 is a control block diagram illustrating a configuration of theresult processor in details;

FIGS. 30 to 42 are views illustrating a particular example in which thedialogue system processes an input, manages a dialogue, and outputs aresult when a user inputs an utterance related to a route guidance;

FIG. 43 is a flowchart illustrating a method of processing a user'sinput in a dialogue processing method in accordance with an embodiment;

FIG. 44 is a flowchart illustrating a method of managing the dialogueusing the output of the input processor in the dialogue processingmethod in accordance with an embodiment;

FIG. 45 is a flowchart illustrating a result processing method forgenerating a response corresponding to a result of the dialoguemanagement in the dialogue processing method in accordance with anembodiment;

FIGS. 46 to 48 is a flowchart illustrating a case in which the dialoguesystem outputs a pre-utterance before a user inputs an utterance in thedialogue processing method in accordance with an embodiment;

FIG. 49 is a flowchart illustrating of processing a duplicate task whenthe dialogue system outputs a pre-utterance before a user inputs anutterance in the dialogue processing method in accordance with anembodiment;

FIG. 50 is a control block diagram illustrating a vehicle gateway methodin which a dialogue system is provided in a remote server and a vehicleacts as a gateway connecting a user to the dialogue system;

FIGS. 51 to 53 are views illustrating a method of acquiring userlabeling context information; and

FIG. 54 is a control block diagram illustrating a vehicle independentmethod in which a dialogue system is provided in a vehicle.

The drawings described herein are for illustration purposes only and arenot intended to limit the scope of the present disclosure in any way.

DETAILED DESCRIPTION

The following description is merely exemplary in nature and is notintended to limit the present disclosure, application, or uses. Itshould be understood that throughout the drawings, correspondingreference numerals indicate like or corresponding parts and features.

In the following description, like reference numerals refer to likeelements throughout the specification. Well-known functions orconstructions are not described in detail since they would obscure theone or more exemplar embodiments with unnecessary detail. Terms such as“unit”, “module”, “member”, and “block” may be embodied as hardware orsoftware. According to embodiments, a plurality of “unit”, “module”,“member”, and “block” may be implemented as a single component or asingle “unit”, “module”, “member”, and “block” may include a pluralityof components.

It will be understood that when an element is referred to as being“connected” another element, it can be directly or indirectly connectedto the other element, wherein the indirect connection includes“connection via a wireless communication network”.

Also, when a part “includes” or “comprises” an element, unless there isa particular description contrary thereto, the part may further includeother elements, not excluding the other elements.

As used herein, the singular forms “a,” “an” and “the” are intended toinclude the plural forms as well, unless the context clearly indicatesotherwise.

An identification code is used for the convenience of the descriptionbut is not intended to illustrate the order of each step. The each stepmay be implemented in the order different from the illustrated orderunless the context clearly indicates otherwise.

Reference will now be made in detail to embodiments of the presentdisclosure, examples of which are illustrated in the accompanyingdrawings.

According to an embodiment, a dialogue system may be configured torecognize a user's intention by using the user's speech and anotherinput except for the speech, and configured to provide a service whichis appropriate or need for the user intention. The dialogue system mayperform dialogue with a user by outputting a system utterance that isone of tools configured to provide the service or to recognize theuser's intention, clearly.

According to embodiments, the service provided to a user may include allkinds of operations in accordance with a user's need or a user'sintention, wherein the all kinds of operations may include providinginformation, controlling a vehicle, performing audio/video/navigationfunctions, and providing content from an external server.

According to an embodiment, the dialogue system provides a dialogueprocessing technology specialized for the vehicle environment so as torecognize the user's intention precisely in a special environment, i.e.a vehicle.

A gateway connecting the dialogue system to a user may be a vehicle or amobile device connected to the vehicle. As mentioned below, the dialoguesystem may be provided in a vehicle or a remote server outside of thevehicle so as to send or receive data through the communication with thevehicle or the mobile device connected to the vehicle.

Some of components in the dialogue system may be provided in the vehicleand some thereof may be provided in the remote server. Therefore, thevehicle and the remote server may perform a part of the operation of thedialogue system.

FIG. 1 is a control block diagram illustrating a dialogue system inaccordance with an embodiment of the present disclosure.

Referring to FIG. 1, a dialogue system 100 may include an inputprocessor 110 processing a user input including a user's speech and aninput except for the user speech, or an input including informationrelated to a vehicle or information related to a user; a dialoguemanager 120 recognizing a user's intention and a vehicle state using aresult of the process of the input processor 110 and determining anaction corresponding to the user's intention or the vehicle state; aresult processor 130 providing a certain service according to an outputresult of the dialogue manager 120 or outputting a system utterance forcontinuing the dialogue; and a storage 140 storing a variety ofinformation for the operation described later.

The input processor 110 may receive two kinds of input such as a userspeech and an input except for the speech. The input except for thespeech may include recognizing user's gesture, an input except for theuser's speech input by an operation of an input device, vehicle stateinformation indicating a vehicle state, driving environment informationrelated to driving information of the vehicle and user informationindicating user's state. In addition, other than the above mentionedinformation, information related to the user and the vehicle may beinput to the input processor 110, as long as information is used forrecognizing a user's intention or providing a service to a user or avehicle. A user may include a driver and a passenger.

The input processor 110 converts a user's speech into an utterance inthe text type by recognizing the user's speech and recognizes a user'sintention by applying natural language understanding algorithm to theuser utterance.

The input processor 110 collects information related to the vehiclestate or the driving environment of the vehicle other than the userspeech, and then understands the context using the collectedinformation.

The input processor 110 transmits the user's intention, which isobtained by the natural language understanding technology, and theinformation related to the context to the dialogue manager 120.

The dialogue manager 120 determines an action corresponding to theuser's intention or the current context based on the user's intentionand the information related to the context transmitted from the inputprocessor 110, and manages parameters that are needed to perform thecorresponding action.

According to embodiments, the action may represent all kinds of actionsfor providing a certain service, and the kinds of the action may bedetermined in advance. As needed, providing a service may correspond toperforming an action.

For example, actions such as a route guidance, a vehicle state check,and gasoline station recommendation may be pre-defined in adomain/action inference rule DB 141 (refer to FIG. 19A), and it may bepossible to extract an action corresponding to a user's utterance, i.e.,an action intended by a user, according to the stored inference rule. Anaction related to an event occurred in the vehicle may be pre-definedand then stored in a relational action DB 146 b (refer to FIG. 21).

There is no limitation in the kinds of the action. If an action isallowed to be performed by the dialogue system 100 via the vehicle 200or the mobile device 400, and is pre-defined while the inference rulethereof or a relation with other action/event is stored, the action maybecome the above mentioned action.

The dialogue manager 120 transmits information related to the determinedaction to the result processor 130.

The result processor 130 generates and outputs a dialogue response and acommand that is needed to perform the transmitted action. The dialogueresponse may be output in text, image or audio type. When the command isoutput, a service such as vehicle control and external contentprovision, corresponding to the output command, may be performed.

The storage 140 stores a variety of information for the dialogueprocessing and the service provision. For example, the storage 140 maypre-store information related to domains, actions, speech acts andentity names used for the natural language understanding and a contextunderstanding table used for understanding the context from the inputinformation. In addition, the storage 140 may pre-store data detected bya sensor provided in the vehicle, information related to a user, andinformation needed for the action. A description of information storedin the storage 140 will be described later.

As mentioned above, the dialogue system 100 provides a dialogueprocessing technology that is specified for the vehicle environment. Allor some of components of the dialogue system 100 may be contained in thevehicle. The dialogue system 100 may be provided in the remote serverand the vehicle may act as a gateway between the dialogue system 100 anda user. In either case, the dialogue system 100 may be connected to theuser via the vehicle or the mobile device connected to the vehicle.

FIG. 2 is a view illustrating an interior of a vehicle.

Referring to FIG. 2, a display 231 configured to display a screenrequired for the control of the vehicle including an audio function, avideo function, a navigation function, and a calling function, and aninput button 221 configured to receive a user's control command may beprovided in a center fascia 203 corresponding to the center portion of adashboard inside of the vehicle 200.

For the user's operation convenience, an input button may be provided ina steering wheel 207 and a jog shuttle 225 acting as an input button maybe provided in a center console region 202 provided between a driverseat 254 a and a passenger seat 254 b.

A module including the display 231, the input button 221 and a processorcontrolling a variety of functions may correspond to an audio videonavigation (AVN) terminal or a head unit.

The display 231 may be implemented by any one of various displaydevices, e.g., Liquid Crystal Display (LCD), Light Emitting Diode (LED),Plasma Display Panel (PDP), Organic Light Emitting Diode (OLED), andCathode Ray Tube (CRT).

The input button 221 may be provided in a hard key type on an areaadjacent to the display 231, as illustrated in FIG. 2. Alternatively,when the display 231 is implemented by a touch screen, the display 231may perform a function of the input button 221.

The vehicle 200 may receive a user control command as a speech via aspeech input device 210. The speech input device 210 may include amicrophone configured to receive the sound and then covert the soundinto an electrical signal.

For the effective speech input, the speech input device 210 may bemounted to a head lining 205, as illustrated in FIG. 2, but anembodiment of the vehicle 200 is not limited thereto. Therefore, thespeech input device 210 may be mounted to the dashboard 201 or thesteering wheel 207. In addition, the speech input device 210 may bemounted to any position as long as a position is appropriate forreceiving the user's speech.

In the inside of the vehicle 200, a speaker 232 configured to performdialogue with a user or configured to output a sound required to providethe service desired by the user may be provided. For example, thespeaker 232 may be provided inside of the driver's seat door 253 a andthe passenger-seat door 253 b.

The speaker 232 may output a speech for navigation route guidance, asound or a speech contained in the audio and video contents, a speechfor providing information or service desired by the user, and a systemutterance generated as a response to the user's utterance.

According to an embodiment, the dialogue system 100 provides a servicethat is appropriate for the user's lifestyle by using the dialogueprocessing technologies appropriate for the vehicle environments, andthe dialogue system 100 may implement a new service using technologiessuch as connected car, Internet of Things (IoT), and artificialintelligence (AI).

When applying the dialogue processing technologies appropriate for thevehicle environments, such as the dialogue system 100 according to anembodiment, it may be easily recognize and respond to a key contextduring a driver directly drives the vehicle. It may be possible toprovide a service by applying a weight to a parameter affecting thedriving, such as gasoline shortages and drowsy driving, or it may bepossible to easily obtain information, e.g., a driving time anddestination information, which is needed for the service, based on acondition in which the vehicle moves to the destination in most cases.

In addition, it may be possible to easily implement intelligent servicesconfigured to provide a function by recognizing a driver's intention.This is because priority is given to real-time information and action inthe driver's direct driving situation. For example, when the driversearches for a gasoline station while driving, it may be interpreted asan intention that the driver will go to the gasoline station. However,when the driver searches for a gasoline station in the place not thevehicle, it may be interpreted as another intention, such as searchingfor location information inquiry, phone number inquiry and price inquiryother than the intention that the driver will go to the gasolinestation.

Further, although the vehicle is a limited space, various situations mayoccur therein. For example, the drive may utilize the dialogue system100 in a variety of situations, e.g., driving a vehicle having anunfamiliar interface, such as a rent car, using chauffeur service, avehicle management situation such as washing vehicle, a situation inwhich a baby is on board, and a situation of visiting a certaindestination.

In addition, a variety of services and dialogue situations may occur ineach stages forming the vehicle driving and the pre and post stage ofthe driving, e.g., a vehicle check stage, a start preparing stage, adriving stage, and a parking stage.

Particularly, the driver may utilize the dialogue system 100 in avariety of situations, e.g., a situation in which a driver does not knowhow to deal with problems, a situation in which the vehicle isassociated with a variety of external devices, a situation of checking adriving habit, e.g., gasoline mileage, and a situation of using safetysupport function, e.g., a smart cruise control, a navigation operationsituation, a drowsy driving situation, a situation of driving along thesame route every day, and a situation of checking whether the place isavailable for parking.

FIGS. 3 to 5 are views illustrating an example of dialogue thatgenerates between a dialogue system and a driver.

Referring to FIG. 3, although the driver does not input an utterance forasking the current remaining amount of gasoline or for requesting agasoline station guidance, the dialogue system 100 may identify thecurrent remaining gasoline by itself and when the identified remaininggasoline is less than a predetermined value, the dialogue system 100 mayfirst output an utterance providing information related to the currentremaining gasoline (S1: it is possible to drive 43 km with the remaininggasoline).

In response to the utterance, the driver may input an utterance asking anear gasoline station to receive a route guidance (U1: let me know anear gasoline station), and the dialogue system 100 may output anutterance providing information related to the nearest gasoline stationfrom the current position (S2: the nearest gasoline stations are A—oilSeong-rim gasoline station, B—oil Jang-dae gasoline station, and C—oilPacific gasoline station.

The driver may additionally input an utterance asking the gasoline price(U2: where is the cheapest?), and the dialogue system 100 may output anutterance providing information related to the price by the fuel type(the lowest price for gasoline is the B oil Jang-dae gasoline station,which costs 1294 won per liter, while the lowest price for diesel is theA oil Seong-rim gasoline station, which costs 985 won per liter).

The driver may input an utterance asking a guidance to the B oilJang-dae gasoline station (U3), and the dialogue system 100 may outputan utterance indicating that the guidance starts to the gasoline stationselected by the driver (S4: a route to the B oil Jang-dae gasolinestation starts).

That is, the dialogue system 100 may determine that the current neededservice is the gasoline guidance service, based on the state informationof the vehicle received via the input processor 110, and output apre-utterance to provide the need service. In addition, the driver maybe guided to the near gasoline station selling the fuel type of thecurrent vehicle at the lowest price, through a dialogue with thedialogue system 100. According to an embodiment, it is assumed that“pre-utterance” represents an utterance that is firstly output from thedialogue system 100 before a user utters.

Meanwhile, when selecting the gasoline station in the example asillustrated in FIG. 3, the dialogue system 100 may omit some questionsand directly provide information and thus it may be possible to reducethe steps and time of the dialogue.

For example, the dialogue system 100 may pre-recognize that the fueltype of the current vehicle is gasoline and criteria of the driver forselecting a gasoline station is price. Information related to the fueltype of the vehicle may be acquired from the vehicle and the criteria ofthe driver for selecting a gasoline station may be pre-input from adriver or acquired by learning the driver dialogue history or thegasoline station selection history. The information may be pre-stored inthe storage 140.

In this case, the dialogue system 100 may proactively output anutterance (S2+S3=S3′) providing information related to the fuel price,particularly the gasoline price which is the fuel type of the currentvehicle without inputting the utterance (U2) for requesting informationabout the fuel price by the driver, i.e., U2 is omitted, as illustratedin FIG. 4.

The driver may omit the utterance (U2) for requesting information aboutthe fuel price and the response of the dialogue system 100 may be formedsuch that the utterance (S2) guiding the near gasoline station and theutterance (S3) guiding the fuel price are integrated as a singleresponse, so as to reduce the steps and time of the dialogue.

In addition, the dialogue system 100 may recognize that the driver'sintention is searching for the gasoline station, by itself, based on thefact that the driver asks the current remaining amount of gasoline.

In this case, as illustrated in FIG. 5, although the driver does notinput the utterance (U1) asking the near gasoline station, i.e., U1 isomitted, the dialogue system 100 may proactively output an utterance(S2+S3=S3″) providing information related to the fuel price.

In a state in which the nearest gasoline station from the currentposition and the gasoline station providing the lowest fuel price is thesame gasoline station, an utterance (S3″) providing information relatedto the fuel price may include a question for asking whether to guide tothe corresponding gasoline station. Therefore, the user may request theroute guidance to the corresponding gasoline station by simply inputtingan utterance agreeing with the question of the dialogue system 100 (U3′:yes), without inputting a particular utterance for asking a guidance toa certain gasoline station.

As mentioned above, the dialogue system 100 may recognize the user'sreal intention and proactively provide information corresponding to theintention by considering a content, which is not uttered by the user,based on pre-obtained information. Therefore, it may be possible toreduce the dialogue steps and time for providing the service desired bythe user.

FIGS. 6 and 7 are control block diagrams schematically illustrating aconnection between the dialogue system and the components of thevehicle.

Referring to FIG. 6, a user's speech input to the dialogue system 100may input via the speech input device 210 provided in the vehicle 200.As illustrated in FIG. 2, the speech input device 210 may include amicrophone provided inside of the vehicle 200.

The input except for the speech in the user input may be input throughan information except for speech input device 220. The informationexcept for speech input device 220 may include an input button 221 and223 and the jog shuttle 225 for receiving a command through theoperation of the user.

The information except for speech input device 220 may include a cameraimaging a user. Through an image imaged by the camera, it is possible torecognize a user's gesture, expression or sight direction which is usedas a tool of command input. Alternatively, it is possible to recognizethe user's state (drowsy state, etc.) through the image imaged by thecamera.

Information related to the vehicle may be input into the dialogue system100 via a vehicle controller 240. Information related to the vehicle mayinclude vehicle state information or surroundings environmentinformation acquired by a variety of sensors provided in the vehicle200, and information which is initially stored in the vehicle 200, e.g.the fuel type of the vehicle.

The dialogue system 100 may recognize the user's intention and contextusing the user's speech input via the speech input device 210, the inputexcept for the user's speech, input via the information except forspeech input device 220, and a variety of information input via thevehicle controller 240. The dialogue system 100 outputs a response toperform an action corresponding to the user's intention.

A dialogue output device 230 is a device configured to provide an outputin a visual, auditory or tactile manner, to a talker. The dialogueoutput device 230 may include the display 231 and the speaker 232provided in the vehicle 200. The display 231 and the speaker 232 mayoutput a response to a user's utterance, a question about a user, orinformation requested by a user, in the visual or auditory manner. Inaddition, it may be possible to output a vibration by installing avibrator in the steering wheel 207.

Further, according to the response output from the dialogue system 100,the vehicle controller 240 may control the vehicle 200 to perform anaction corresponding to the user's intention or the current situation.

Meanwhile, as well as the information acquired by the sensor provided inthe vehicle 200, the vehicle 200 may collect information acquired froman external content server 300 or an external device via thecommunication device 280, e.g., driving environment information and userinformation such as traffic conditions, weather, temperature, passengerinformation and driver personal information, and then the vehicle 200may transmit the information to the dialogue system 100.

As illustrated in FIG. 7, information acquired by the sensor provided inthe vehicle 200, e.g., a remaining amount of fuel, an amount of rain, arain speed, surrounding obstacle information, a speed, an enginetemperature, a tire pressure, current position, may be input to thedialogue system 100 via an internal signal controller 241.

The driving environment information acquired from the outside viaVehicle to Everything (V2X) communication may be input to the dialoguesystem 100 via an external signal controller 242. The V2X may representthat a vehicle exchanges and shares a variety of useful information,e.g. traffic condition, by communicating with a road infrastructure andother vehicle during driving.

The V2X communication may include Vehicle-to Infrastructure (V2I)communication, Vehicle-to-Vehicle (V2V) communication, andVehicle-to-Nomadic devices (V2N) communication. Therefore, by using theV2X communication, it may be possible to send and receive informationsuch as traffic information about the front side or an access of anothervehicle or risk of collision with another vehicle through thecommunication directly performed between vehicles or the communicationwith the infrastructure installed in the road and thus it may bepossible to inform a driver of the information.

Therefore, the driving environment information input to the dialoguesystem 100 via the external signal controller 242 may include trafficinformation about the front side, access information of adjacentvehicle, collision warning with another vehicle, real time trafficconditions, unexpected conditions, and a traffic flow control state.

Although not shown in the drawings, signals obtained via V2X may also beinput to the vehicle 200 via the communication device 280.

The vehicle controller 240 may include a memory in which a program forperforming the above-described operation and the operation describedlater is stored, and a processor for executing the stored program. Atleast one memory and one processor may be provided, and when a pluralityof memory and processors are provided, they may be integrated on onechip or physically separated.

In addition, the internal signal controller 241 and the external signalcontroller 242 may be implemented by the same processor and memory or bya separate processor and memory.

FIGS. 8 and 9 are control block diagrams schematically illustrating aconnection between the dialogue system and the components of thevehicle.

Referring to FIG. 8, the user's speech transmitted from the speech inputdevice 210 may be input to a speech input processor 111 provided in theinput processor 110, the input except for the user's speech transmittedfrom the information except for speech input device 220 may be input toa context information processor 112 provided in the input processor 110.

In addition, information that is input via the internal signalcontroller 241 or the external signal controller 242 is input to thecontext information processor 112 provided in the input processor 110.

The context information input to the context information processor 112may include the vehicle state information, the driving environmentinformation and the user information, which is input from theinformation except for speech input device 220 and the vehiclecontroller 240. The context information processor 112 may identify thecontext based on the input context information. The dialogue system 100may precisely recognize the user's intention or efficiently find out aservice needed for the user, by identifying the context.

A response output from the result processor 130 may input to thedialogue output device 230 or the vehicle controller 240 to allow thevehicle 200 to provide the service needed for the user. In addition, theresponse may be transmitted to the external content server 300 torequest the needed service.

The vehicle state information, the driving environment information andthe user information transmitted from the vehicle controller 240 may bestored in the storage 140.

Referring to FIG. 9, the storage 140 may include a long-term memory 143and a short-term memory 144. Data stored in the storage 140 may beclassified into the short term memory and the long term memory accordingto the importance and the persistence of the data, and the designer'sintention.

The short-term memory 144 may store the dialogue that is previouslyperformed. The previous dialogue may be a dialogue performed within areference time from the current. Alternatively, the dialogue may becontinuously stored until the capacity of the utterance content betweenthe user and the dialogue system 100 becomes a reference value.

For example, when it is time for meal, the vehicle 200 may output anutterance asking whether to guide a restaurant, via the speaker 232.Whether it is time for meal may be identified based on whether a currenttime is within a predetermined meal time range. When the user utters acontent “let me know a restaurant near Gangnam Station” or a content“let me know a restaurant” and when the current position of the vehicle200 is around Gangnam Station, the dialogue system 100 may search forrestaurants near Gangnam Station through the external content server 300and then provide information related to the searched restaurant nearGangnam Station, to the user. An example of providing information, thedialogue system 100 may display a list of the restaurant on the display231 and when the user utters “first”, the dialogue content related tothe request of the restaurant to the selection of the restaurant may bestored in the short-term memory 144.

Alternatively, not only the entire dialogue contents are stored, butalso specific information contained in the dialogue contents may bestored. For example, it is possible to store the first restaurant of therestaurant list in the short-term memory 144 or the long-term memory 143as a restaurant selected by the user.

When the user asks “How is the weather?” to the dialogue system 100after the dialogue about the restaurant near Gangnam Station, thedialogue system 100 may assume that a user's interest location isGangnam Station, from the dialogue stored in the short-term memory 144and then output a response “it is raining in Gangnam Station”

Next, when the user utters “recommend a menu of the restaurant”, thedialogue system 100 may assume that “the restaurant” represents arestaurant near Gangnam Station, from the dialogue stored in the shortterm memory, and acquire information related to a recommend menu of thecorresponding restaurant through the service provided from the externalcontent server 300. Accordingly, the dialogue system 100 may output theresponse “noodle is the best menu in the restaurant.”

The long-term memory 143 may store data according to the presence of thepersistence of the data. For example, the long-term memory 143 maydetermine that the persistence of the data such as position of interest(POI) information, e.g., family and friend telephone numbers and home orcompany, and user preferences for certain parameters is secured and thenstore the data therein. In contrast, when it is determined that thepersistence of the data is not secured, the data may be stored in theshort-term memory 144.

For example, the current location of the user may be a temporary dataand thus stored in the short-term memory 144 and the user's preferencefor the restaurant may be a persistent data which is available later andthus stored in the long-term memory 143.

When the user utters “is there any restaurant around here?”, thedialogue system 100 may recognize the current location of the user andfigure out that the user prefers the Chinese restaurant, from thelong-term memory 143. Therefore, the dialogue system 100 may recommendthe list of user's favorite Chinese restaurant around the currentlocation, by using the external content.

In addition, the dialogue system 100 may proactively provide service andinformation to the user using the data stored in the long-term memory143 and the short-term memory 144.

For example, information related to the user's house may be stored inthe long-term memory 143. The dialogue system 100 may acquire theinformation related to the user's house, from the external contentserver 300, and then provide information indicating “a water outage isexpected this Fri day due to the cleaning of Apartment”

Information related to a vehicle battery state may be stored in theshort-term memory 144. The dialogue system 100 may analyze the vehiclebattery state stored in the short-term memory 144 and then provideinformation indicating “the battery is in the bad condition. Have itrepaired before winter.”

FIG. 10 is a control block diagram illustrating a vehicle independentmethod in which a dialogue system is provided in a vehicle.

According to the vehicle independent method, the dialogue system 100having the input processor 110, the dialogue manager 120, the resultprocessor 130 and the storage 140 may be contained in the vehicle 200,as illustrated in FIG. 10.

When the dialogue system 100 is contained in the vehicle 200, thevehicle 200 may process dialogue with a user, by itself and provide aservice needed for the user. However, the information needed for thedialogue processing and service provision may be brought from theexternal content server 300.

The vehicle state information or the driving environment information,e.g., an remaining amount of fuel, an amount of rain, a rain speed,surrounding obstacle information, a speed, an engine temperature, a tirepressure, current position, which is detected by a vehicle detector 260may be input to the dialogue system 100 via the vehicle controller 240.

According to a response output from the dialogue system 100, the vehiclecontroller 240 may control the air conditioning device 251, the window252, the door 253, the seat 254 or the AVN 255 provided in the vehicle200.

For example, when the dialogue system 100 determines that the user'sintention or the service needed for the user is to lower the temperatureinside the vehicle 200 and then generates and outputs a correspondingcommand, the vehicle controller 240 may lower the temperature inside thevehicle 200 by controlling the air conditioner 251.

For another example, when the dialogue system 100 determines that theuser's intention or the service needed for the user is to raise thedriver's seat window 252 a and generates and outputs a correspondingcommand, the vehicle controller 240 may raise the driver's seat window252 a by controlling the window 252.

For another example, when the dialogue system 100 determines that theuser's intention or the service needed for the user is to guide a routeto a certain destination and generates and outputs a correspondingcommand, the vehicle controller 240 may perform a route guidance bycontrolling the AVN 255. As needed, the communication device 280 maybring map data, and POI information from the external content server 300and then use the information for the service provision.

FIGS. 11 and 12 are control block diagrams illustrating a vehiclegateway method in which a dialogue system is provided in a remote serverand a vehicle acts as a gateway connecting a user to the dialoguesystem.

According to the vehicle gateway method, as illustrated in FIG. 11, aremote dialogue system server 1 may be provided in the outside of thevehicle 200, and a dialogue system client 270 connected via the remotedialogue system server 1 and the communication device 280 may beprovided in the vehicle 200. The communication device 280 serves as agateway for connecting the vehicle 200 and the remote dialogue systemserver 1.

The dialogue system client 270 may serve as an interface connected to aninput/output device and perform collecting, and sending and receivingdata.

When the speech input device 210 and the information except for speechinput device 220 provided in the vehicle 200 receive a user's input andtransmit the user input to the dialogue system client 270, the dialoguesystem client 270 may transmit the input data to the remote dialoguesystem server 1 via the communication device 280.

The vehicle controller 240 may also transmit data detected by thevehicle detector 260 to the dialogue system client 270 and the dialoguesystem client 270 may transmit the data detected by the vehicle detector260 to the remote dialogue system server 1 via the communication device280.

Since the above mentioned dialogue system 100 is provided in the remotedialogue system server 1, the remote dialogue system server 1 mayperform all of input data processing, dialogue processing based on theresult of the input data processing, and result processing based on theresult of the dialogue processing.

In addition, the remote dialogue system server 1 may bring informationor content needed for the input data processing, the dialoguemanagement, or the result processing, from the external content server300.

According to a response transmitted from the remote dialogue systemserver 1, the vehicle 200 may bring information or content for theservice needed for the user from the external content server 300.

Referring to FIG. 12, the communication device 280 may include at leastone communication module configured to communicate with an externaldevice. For example, the communication device 280 may include at leastone of a short range communication module 281, a wired communicationmodule 282, and a wireless communication module 283.

The short-range communication module 281 may include a variety of shortrange communication modules, which is configured to transmit and receivea signal using a wireless communication module in the short range, e.g.,Bluetooth module, Infrared communication module, Radio FrequencyIdentification (RFID) communication module, Wireless Local AccessNetwork (WLAN) communication module, NFC communications module, andZigBee communication module.

The wired communication module 282 may include a variety of wiredcommunication module, e.g., Local Area Network (LAN) module, Wide AreaNetwork (WAN) module, or Value Added Network (VAN) module and a varietyof cable communication module, e.g., Universal Serial Bus (USB), HighDefinition Multimedia Interface (HDMI), Digital Visual Interface (DVI),recommended standard 232 (RS-232), power line communication or plain oldtelephone service (POTS).

The wireless communication module 283 may include a wirelesscommunication module supporting a variety of wireless communicationmethods, e.g., Wifi module, Wireless broadband module, global System forMobile (GSM) Communication, Code Division Multiple Access (CDMA),Wideband Code Division Multiple Access (WCDMA), Time Division MultipleAccess (TDMA), Long Term Evolution (LTE), 4G and 5G.

In addition, the communication device 280 may further include aninternal communication module (not shown) for communication betweenelectronic devices in the vehicle 200. The communication protocol of thevehicle 200 may use Controller Area Network (CAN), Local InterconnectionNetwork (LIN), FlexRay, and Ethernet.

The dialogue system 100 may send and receive data to and from theexternal content server 300 or the remote dialogue system server 1 viathe wireless communication module 283. The dialogue system 100 mayperform the V2X communication using the wireless communication module283. In addition, using the short range communication module 281 or thewired communication module 282, the dialogue system 100 may send andreceive data to and from a mobile device connected to the vehicle 200.

FIG. 13 is a control block diagram illustrating a case in which thevehicle can perform some input processing and output processing in thevehicle gateway method.

As mentioned above, the dialogue system client 270 of the vehicle 200may only collect and send and receive the data but the dialogue systemclient 270 may process data input from the user or the vehicle orperform a processing related to the service provision that is determinedto be needed to the user, since an input processor 271, a resultprocessor 273 and a storage 274 are contained in the dialogue systemclient 270, as illustrated in FIG. 13. That is, the operation of theinput processor 110 and the result processor 130 may be performed by notonly the remote dialogue system server 1 but also the vehicle 200.

In this case, the dialogue system client 270 may perform all or someoperation of the input processor 110. The dialogue system client 270 mayperform all or some operation of the result processor 130.

The task sharing between the remote dialogue system server 1 and thedialogue system client 270 may be determined in consideration of thecapacity of the data to be processed and the data processing speed.

FIG. 14 is a control block diagram illustrating a hybrid method in whichboth of a remote dialogue system server and a vehicle perform a dialogueprocessing.

According to the hybrid method, as illustrated in FIG. 14, since theinput processor 110, the dialogue manager 120, the result processor 130and the storage 140 are provided in the remote dialogue system server 1,the remote dialogue system server 1 may perform the dialogue processing,and since a terminal dialogue system 290 provided with an inputprocessor 291, a dialogue manager 292, a result processor 293 and astorage 294 is provided in the vehicle 200, the vehicle 200 may performthe dialogue processing.

However, there may be difference between a processor and a memoryprovided in the vehicle 200 and a processor or a memory provided in theremote dialogue system server 1 in the capacity or performance.Accordingly, when the terminal dialogue system 290 is capable ofoutputting a result by processing all the input data and managing thedialogue, the terminal dialogue system 290 may perform the entireprocess. Otherwise, it may be possible to request the processing to theremote dialogue system server 1.

Before performing the dialogue processing, the terminal dialogue system290 may determine whether it is possible to perform the dialogueprocessing based on the data type, and the terminal dialogue system 290may directly perform the processing or request the processing to theremote dialogue system server 1 based on the result of thedetermination.

When an event occurs in which the terminal dialogue system 290 cannotperform the process during performing the dialogue process, the terminaldialogue system 290 may request the processing to the remote dialoguesystem server 1 while transmitting a result that is processed by itself,to the remote dialogue system server 1.

For example, when the high-performance computing power or the long-termdata processing is needed, the remote dialogue system server 1 mayperform a dialogue processing and when the real time processing isneeded, the terminal dialogue system 290 may perform the dialogueprocessing. For example, when an instant requiring immediate processingoccurs and thus it is needed to process the data before thesynchronization, it may be set such that the terminal dialogue system290 firstly processes the data.

In addition, when there is an unregistered talker in the vehicle andthus a user confirmation is required, the remote dialogue system server1 may process the dialogue.

Further, when the terminal dialogue system 290 is unable to complete thedialogue processing by itself in a state in which the connection withthe remote dialogue system server 1 via the communication device 280 isnot allowed, it may be possible to inform a user that the dialogueprocessing cannot be performed, via the dialogue output device 230.

Data stored in the terminal dialogue system 290 and data stored in theremote dialogue system server 1 may be determined according to the datatype or the data capacity. For example, in the case of data having arisk of invasion of privacy because of personal identification, the datamay be stored in the storage 294 of the terminal dialogue system 290. Inaddition, a large amount of data may be stored in the storage 140 of theremote dialogue system server 1, and a small amount of data may bestored in the storage 294 of the terminal dialogue system 290.Alternatively, a small amount of data may be stored in both of thestorage 140 of the remote dialogue system server 1 and the storage 294of the terminal dialogue system 290.

FIGS. 15 and 16 are control block diagrams illustrating a mobile gatewaymethod in which a mobile device connected to a vehicle connects a userto a remote dialogue system server.

According to the mobile gateway method, as illustrated in FIG. 15, themobile device 400 may receive the vehicle state information and thedriving environment information, etc. from the vehicle 200, and transmitthe user input and the vehicle state information to the remote dialoguesystem server 1. That is, the mobile device 400 may act as a gatewayconnecting a user to the remote dialogue system server 1 or connectingthe vehicle 200 to the remote dialogue system server 1.

The mobile device 400 may represent an electronic device that isportable and capable of sending and receiving data to and from anexternal server and a vehicle by communicating with the external serverand vehicle, wherein the mobile device 400 may include a smart phone, asmart watch, a smart glass, a PDA, and a tablet PC.

The mobile device 400 may include a speech input device 410 receiving auser's speech, an except for speech input device 420 receiving an inputexcept for the user' speech, an output device 430 outputting a responsein a visual, auditory or tactile manner, a communication device 480sending and receiving data to and from the remote dialogue system server1 and the vehicle 200 through the communication, and a dialogue systemclient 470 collecting input data from a user and transmitting the datato the remote dialogue system server 1 via the communication device 480.

The speech input device 410 may include a microphone receiving sound,converting the sound into an electrical signal and outputting theelectrical signal.

The except for speech input device 420 may include an input button, atouch screen or a camera provided in the mobile device 400.

The output device 430 may include a display, a speaker or a vibratorprovided in the mobile device 400.

The speech input device 410, the except for speech input device 420 andthe output device 430 provided in the mobile device 400 may serve as aninput and output interface for a user. In addition, the speech inputdevice 210, the information except for speech input device 220, thedialogue output device 230 provided in the vehicle 200 may serve as aninput and output interface for a user.

When the vehicle 200 transmits data detected by the vehicle detector 260and the user input to the mobile device 400, the dialogue system client470 of the mobile device 400 may transmit the data and the user input tothe remote dialogue system server 1.

The dialogue system client 470 may transmit a response or a commandtransmitted from the remote dialogue system server 1, to the vehicle200. When the dialogue system client 470 uses the dialogue output device230 provided in the vehicle 200 as the input and output interface forthe user, an utterance of the dialogue system 100 or a response to auser's utterance via may be output via the dialogue output device 230.When the dialogue system client 470 uses the output device 430 that isprovided in the mobile device 400, an utterance of the dialogue system100 or a response to a user's utterance may be output via the outputdevice 430.

The command for the vehicle control may be transmitted to the vehicle200 and the vehicle controller 240 may perform a control correspondingto the transmitted command, thereby providing the service needed for theuser.

The dialogue system client 470 may collect the input data and transmitthe input data to the remote dialogue system server 1. The dialoguesystem client 470 may also perform all or some function of the inputprocessor 110 and the result processor 130 of the dialogue system 100.

Referring to FIG. 16, the communication device 480 of the mobile device400 may include at least one communication module configured tocommunicate with an external device. For example, the communicationdevice 480 may include at least one of a short range communicationmodule 481, a wired communication module 482, and a wirelesscommunication module 483.

The short-range communication module 481 may include a variety of shortrange communication modules, which is configured to transmit and receivea signal using a wireless communication module in the short range, e.g.,Bluetooth module, Infrared communication module, Radio FrequencyIdentification (RFID) communication module, Wireless Local AccessNetwork (WLAN) communication module, NFC communications module, andZigBee communication module.

The wired communication module 482 may include a variety of wiredcommunication module, e.g., Local Area Network (LAN) module, Wide AreaNetwork (WAN) module, or Value Added Network (VAN) module and a varietyof cable communication module, e.g., Universal Serial Bus (USB), HighDefinition Multimedia Interface (HDMI), Digital Visual Interface (DVI),recommended standard 232 (RS-232), power line communication or plain oldtelephone service (POTS).

The wireless communication module 483 may include a wirelesscommunication module supporting a variety of wireless communicationmethods, e.g., Wifi module, Wireless broadband module, global System forMobile (GSM) Communication, Code Division Multiple Access (CDMA),Wideband Code Division Multiple Access (WCDMA), Time Division MultipleAccess (TDMA), Long Term Evolution (LTE), 4G and 5G.

For example, the mobile device 400 may be connected to the vehicle 200via the short range communication module 481 or the wired communicationmodule 482, and the mobile device 400 may be connected to the remotedialogue system server 1 or the external content server 300 via thewireless communication module 483.

FIG. 17 is a control block diagram illustrating a mobile independentmethod in which a dialogue system is provided in a mobile device.

According to the mobile independent method, as illustrated in FIG. 17,the dialogue system 100 may be provided in the mobile device 400.

Therefore, without being connected to the remote dialogue system server1 for the dialogue processing, the mobile device 400 may processdialogue with a user and provide a service needed for the user, byitself. However, the mobile device 400 may bring one piece of theinformation for the dialogue processing and service provision, from theexternal content server 300.

According to any method of the above-mentioned methods, componentsforming the dialogue system 100 may be physically separated from eachother or some of the components may be omitted. For example, even whenthe dialogue system 100 is provided in the remote dialogue system server1, some of components forming the dialogue system 100 may be provided ina separate server or the vehicle. An operator or a manger of theseparate server may be the same as or different from that of the remotedialogue system server 1. For example, a speech recognizer or a naturallanguage understanding portion described later may be provided in theseparate server and the dialogue system 100 may receive a result ofspeech recognition or a result of natural language understanding about auser's utterance, from the separate server. Alternatively, the storage140 may be provided in the separate server.

A description of the detailed configuration and detailed operation ofeach component of the dialogue system 100 will be described in detail.According to an embodiment described later, for convenience ofexplanation, it is assumed that the dialogue system 100 is provided inthe vehicle 200. Specific components of the dialogue system 100described later may be classified according to an operation thereof, andthere may be no limitation on whether the components is implemented bythe same processor and memory or not and a physical position of theprocessor memory.

FIGS. 18, 19A and 19B are control block diagrams illustrating aconfiguration of an input processor in the configuration of the dialoguesystem in detail.

Referring to FIG. 18, the input processor 110 may include the speechinput processor 111 processing the speech input and the contextinformation processor 112 processing the context information.

The user's speech transmitted from the speech input device 210 may beinput to the speech input processor 111 and the input except for theuser's speech transmitted from the information except for speech inputdevice 220 may be input to the context information processor 112.

The vehicle controller 240 may transmit the vehicle state information,the driving environment information and the user information to thecontext information processor 112. The driving environment informationand the user information may be provided to the external content server300 or the mobile device 400 connected to or the vehicle 200.

The input except for the speech may be contained in the contextinformation. That is, the context information may include the vehiclestate information, the driving environment information and the userinformation.

The vehicle state information may include information, which indicatesthe vehicle state and is acquired by a sensor provided in the vehicle200, and information that is related to the vehicle, e.g., the fuel typeof the vehicle, and stored in the vehicle.

The driving environment information may be information acquired by asensor provided in the vehicle 200. The driving environment informationmay include image information acquired by a front camera, a rear cameraor a stereo camera, obstacle information acquired by a sensor, e.g., aradar, a Lidar, an ultrasonic sensor, and information related to anamount of rain, and rain speed information acquired by a rain sensor.

The driving environment information may further include traffic stateinformation, traffic light information, and adjacent vehicle access oradjacent vehicle collision risk information, which is acquired via theV2X.

The user information may include information related to user state thatis measured by a camera provided in the vehicle or a biometric reader,information related to a user that is directly input using an inputdevice provided in the vehicle by the user, information related to auser and stored in the external content server 300, and informationstored in the mobile device 400 connected to the vehicle.

The speech input processor 111 may include an speech recognizer 111 aoutputting an utterance in the text type by recognizing the input user'sspeech, a natural language understanding portion 111 b identifying theuser's intention contained in the utterance by applying natural languageunderstanding technology to the user utterance, and a dialogue inputmanager 111 c transmitting a result of the natural languageunderstanding and the context information, to the dialogue manager 120.

The speech recognizer 111 a may include a speech recognition engine andthe speech recognition engine may recognize a speech uttered by a userby applying a speech recognition algorithm to the input speech andgenerate a recognition result.

Since the input speech is converted into a more useful form for thespeech recognition, the speech recognizer 111 a may detect an actualspeech section included in the speech by detecting a start point and anend point from the speech signal. This is called End Point Detection(EPD).

The speech recognizer 111 a may extract the feature vector of the inputspeech from the detected section by applying the feature vectorextraction technique, e.g., Cepstrum, Linear Predictive Coefficient:(LPC), Mel Frequency Cepstral Coefficient (MFCC) or Filter Bank Energy.

The speech recognizer 111 a may acquire the results of recognition bycomparing the extracted feature vector with a trained reference pattern.At this time, the speech recognizer 111 a may use an acoustic model ofmodeling and comparing the signal features of a speech, and a languagemodel of modeling a linguistic order relation of a word or a syllablecorresponding to a recognition vocabulary. For this, the storage 140 maystore the acoustic model and language model DB.

The acoustic model may be classified into a direct comparison method ofsetting a recognition target to a feature vector model and comparing thefeature vector model to a feature vector of a speech signal, and astatistical method of statistically processing a feature vector of arecognition target.

The direct comparison method is setting a unit, such as a word or aphoneme, which is a recognition target, to a feature vector model, andcomparing a received speech to the feature vector model to determinesimilarity between them. A representative example of the directcomparison method is vector quantization. The vector quantization ismapping feature vectors of a received speech signal to a codebook thatis a reference model to code the results of the mapping torepresentative values, and comparing the representative values to eachother.

The statistical model method is configuring units of a recognitiontarget as state sequences and using a relationship between the statesequences. Each state sequence may be configured with a plurality ofnodes. The method of using the relationship between the state sequencescan be classified into Dynamic Time Warping (DTW), Hidden Markov Model(HMM), and a method of using a neural network.

The DTW is a method of compensating for differences in the time axisthrough comparison to a reference model in consideration of the dynamicfeature of speech that the length of a signal varies over time even whenthe same person utters the same pronunciation. The HMM is a recognitionmethod of assuming a speech as a Markov process having state transitionprobability and observation probability of nodes (output symbols) ineach state, then estimating state transition probability and observationprobability of nodes based on learning data, and calculating probabilityat which a received speech is to be generated from an estimated model.

Meanwhile, the language model of modeling a linguistic order relation ofa word, a syllable, etc. may reduce acoustic ambiguity and recognitionerrors by applying an order relation between units configuring alanguage to units acquired through speech recognition. The languagemodel may include a statistical language model, and a model based onFinite State Automata (FSA). The statistical language model uses chainprobability of a word, such as Unigram, Bigram, and Trigram.

The speech recognizer 111 a may use any one of the above-describedmethods for the speech recognition. For example, the speech recognizer111 a may use an acoustic model to which the HMM is applied, or a N-bestsearch method in which an acoustic model is combined with a speechmodel. The N-best search method can improve recognition performance byselecting N recognition result candidates or less using an acousticmodel and a language model, and then re-estimating an order of therecognition result candidates.

The speech recognizer 111 a may calculate a confidence value to ensurereliability of a recognition result. A confidence value may be criteriarepresenting how a speech recognition result is reliable. For example,the confidence value may be defined, with respect to a phoneme or a wordthat is a recognized result, as a relative value of probability at whichthe corresponding phoneme or word has been uttered from differentphonemes or words. Accordingly, a confidence value may be expressed as avalue between 0 and 1 or between 1 and 100.

When the confidence value is greater than a predetermined thresholdvalue, the speech recognizer 111 a may output the recognition result toallow an operation corresponding to the recognition result to beperformed. When the confidence value is equal to or less than thethreshold value, the speech recognizer 111 a may reject the recognitionresult.

The utterance in the form of text that is the recognition result of thespeech recognizer 111 a may be input to the natural languageunderstanding portion 111 b.

The natural language understanding portion 111 b may identify anintention of user's utterance included in an utterance language byapplying the natural language understanding technology. Therefore, theuser may input a control command through a natural dialogue, and thedialogue system 100 may also induce the input of the control command andprovide a service needed the user via the dialogue.

The natural language understanding portion 111 b may performmorphological analysis on the utterance in the form of text. A morphemeis the smallest unit of meaning and represents the smallest semanticelement that can no longer be subdivided. Thus, the morphologicalanalysis is a first step in natural language understanding andtransforms the input string into the morpheme string.

The natural language understanding portion 111 b may extract a domainfrom the utterance based on the morphological analysis result. Thedomain may be used to identify a subject of a user utterance language,and the domain indicating a variety of subjects, e.g., route guidance,weather search, traffic search, schedule management, fuel management andair conditioning control, may be stored as a database.

The natural language understanding portion 111 b may recognize an entityname from the utterance. The entity name may be a proper noun, e.g.,people names, place names, organization names, time, date, and currency,and the entity name recognition may be configured to identify an entityname in a sentence and determine the type of the identified entity name.The natural language understanding portion 111 b may extract importantkeywords from the sentence using the entity name recognition andrecognize the meaning of the sentence.

The natural language understanding portion 111 b may analyze a speechact contained in the utterance. The speech act analysis may beconfigured to identify the intention of the user utterance, e.g.,whether a user asks a question, whether a user asks a request, whether auser responses or whether a user simply expresses an emotion.

The natural language understanding portion 111 b extracts an actioncorresponding to the intention of the user's utterance. The naturallanguage understanding portion 111 b may identify the intention of theuser's utterance based on the information, e.g., domain, entity name,and speech act and extract an action corresponding to the utterance. Theaction may be defined by an object and an operator.

The natural language understanding portion 111 b may extract a parameterrelated to the action execution. The parameter related to the actionexecution may be an effective parameter that is directly required forthe action execution, or an ineffective parameter that is used toextract the effective parameter.

For example, when a user's utterance is “let's go to Seoul station”, thenatural language understanding portion 111 b may extract “navigation” asa domain corresponding to the utterance, and “route guidance” as anaction, wherein a speech act corresponds to “request”.

The entity name “Seoul station” may correspond to [parameter:destination] related to the action execution, but a specific exit numberof the station or GPS information may be required to practically guide aroute via the navigation system. In this case, [parameter: destination:Seoul station] extracted by the natural language understanding portion111 b may be a candidate parameter for searching “Seoul station” that isactually desired by the user among a plurality of Seoul station POI.

The natural language understanding portion 111 b may extract a toolconfigured to express a relationship between words or between sentences,e.g., parse-tree.

The morphological analysis result, the domain information, the actioninformation, the speech act information, the extracted parameterinformation, the entity name information and the parse-tree, which isthe processing result of the natural language understanding portion 111b may be transmitted to the dialogue input manager 111 c.

The context information processor 112 may include a context informationcollector 112 a collecting information from the information except forspeech input device 220 and the vehicle controller 240, a contextinformation collection manager 112 b managing the collection of thecontext information, and a context understanding portion 112 cunderstanding context based on the result of the natural languageunderstanding and the collected context information.

The input processor 110 may include a memory in which a program forperforming the above-described operation and the operation describedlater is stored, and a processor for executing the stored program. Atleast one memory and one processor may be provided, and when a pluralityof memory and processors are provided, they may be integrated on onechip or physically separated.

The speech input processor 111 and the context information processor 112contained in the input processor 110 may be implemented by the sameprocessor and memory or a separate processor and memory.

Hereinafter, a method in which components of the input processor 110process the input data using information stored in the storage 140 willbe described in detail with reference to FIGS. 19A and 19B.

Referring to FIG. 19A, the natural language understanding portion 111 bmay use the domain/action inference rule DB 141 for the domainextraction, entity recognition, the speech act analysis and the actionextraction.

In the domain/action inference rule DB 141, domain extraction rules,speech act analysis rules, entity name conversion rules, actionextraction rules may be stored.

Other information such as the user input except for the speech, thevehicle state information, the driving environment information and theuser information may be input to the context information collector 112 aand then stored in a context information DB 142, the long-term memory143, or the short-term memory 144.

For example, raw data detected by the vehicle detector 260 may beclassified into a sensor type and a sensor value and then stored in thecontext information DB 142.

In the short-term memory 144 and long-term memory 143, data that ismeaningful to the user may be stored, wherein the data may include thecurrent user state, the user's preference and orientation or data fordetermining the user's preference and orientation.

As described above, information that ensures the persistence and thus isusable in the long term, may be stored in the long-term memory 143,wherein the information may include the user's phone book, schedule,preferences, educational history, personality, job, and informationrelated to family.

Information that does not ensure the persistence or has uncertaintiesand thus is usable in the short term may be stored in the short-termmemory 144, wherein the information may include the current and previousposition, today schedule, the previous dialogue content, dialogueparticipants, circumstances, domains, and driver state. According todata type, there may be data stored in at least two storages among thecontext information DB 142, the short-term memory 144 and the long-termmemory 143 in duplicate.

In addition, among the information stored in the short-term memory 144,data, which is determined to ensure the persistence, may be transmittedto the long-term memory 143.

It may be possible to acquire information to be stored in the long-termmemory 143 using information stored in the short-term memory 144 and thecontext information DB 142. For example, the user's preference may beacquired by analyzing destination information that is stored for certainduration or the dialogue content, and the acquired user's preference maybe stored in the long-term memory 143.

By using information stored in the short-term memory 144 or the contextinformation DB 142, it may be performed to obtain information to bestored in the long-term memory 143 in the dialogue system 100, or in anadditional external system.

It may possible to perform the former case in the memory manager 135 ofthe result processor 130. In this case, among the data stored in theshort-term memory 144 or the context information DB 142, data used toacquire meaningful information, e.g., the user's preference ororientation or persistent information may be stored in the long-termmemory 143 in the log file type. The memory manager 135 may acquirepersistent data by analyzing data that is stored for more than certainduration, and re-sore the data in the long-term memory 143. In thelong-term memory 143, a location in which the persistent data is storedmay be different from a location in which the data stored in the logfile type is stored.

The memory manager 135 may determine persistent data among data storedin the short-term memory 144 and move and store the determined data toand in the long-term memory 143.

When obtaining information to be stored in the long-term memory 143using information stored in the short-term memory 144 or the contextinformation DB 142 is performed in the an additional external system, adata management system 800 provided with a communicator 810, a storage820 and a controller 830 may be used, as illustrated in FIG. 19B.

The communicator 810 may receive data stored in the context informationDB 142 or the short-term memory 144. All data stored may be transmittedto the communicator 810 or the data used to acquire meaningfulinformation, e.g., the user's preference or orientation or persistentinformation may be selected and then transmitted. The received data maybe stored in the storage 820.

The controller 830 may acquire the persistent data by analyzing thestored data and then transmit the acquired data to the dialogue system100 via the communicator 810. The transmitted data may be stored in thelong-term memory 143 of the dialogue system 100.

In addition, the dialogue input manager 111 c may acquire contextinformation related to the action execution by transmitting the resultof the output of the natural language understanding portion 111 b to thecontext understanding portion 112 c.

The context understanding portion 112 c may determine which contextinformation is related to the action execution corresponding to theintention of the user's utterance, by referring to context informationthat is stored according to the action in a context understating table145.

FIGS. 20A and 20B are views illustrating an example of informationstored in a context understanding table.

Referring to an example of FIG. 20A, context information and the type ofthe context information related to the action execution may be stored inthe context understating table 145 according to each action.

For example, when the action is route guidance, the current position maybe needed as the context information and the type of the contextinformation may be GPS information. When the action is vehicle statecheck, distance traveled may be needed as the context information andthe type of the context information may be integer. When the action isgasoline station recommendation, an amount of remaining fuel anddistance to empty (DTE) may be needed as the context information and thetype of the context information may be integer.

When context information related to the action execution correspondingto the intention of the user's utterance is pre-stored in the contextinformation DB 142, the long-term memory 143 or the short-term memory144, the context understanding portion 112 c may bring the correspondinginformation from the context information DB 142, the long-term memory143 or the short-term memory 144 and transmit the correspondinginformation to the dialogue input manager 111 c.

When context information related to the action execution correspondingto the intention of the user's utterance is not stored in the contextinformation DB 142, the long-term memory 143 or the short-term memory144, the context understanding portion 112 c may request neededinformation to the context information collection manager 112 b. Thecontext information collection manager 112 b may allow the contextinformation collector 112 a to collect the needed information.

The context information collector 112 a may periodically collect data,or collect data only when a certain event occurs. In addition thecontext information collector 112 a may periodically collect data andthen additionally collect data when a certain event occurs. Further,when receiving a data collection request from the context informationcollection manager 112 b, the context information collector 112 a maycollect data.

The context information collector 112 a may collect the neededinformation and then store the information in the context information DB142 or the short-term memory 144. The context information collector 112a may transmit a confirmation signal to the context informationcollection manager 112 b.

The context information collection manager 112 b may transmit theconfirmation signal to the context understanding portion 112 c and thecontext understanding portion 112 c may bring the needed informationfrom the long-term memory 143 or the short-term memory 144 and thentransmit the information to the dialogue input manager 111 c.

Particularly, when the action corresponding to the intention of theuser's utterance is the route guidance, the context understandingportion 112 c may search the context understating table 145 andrecognize that context information related to the route guidance is thecurrent position.

When the current position is pre-stored in the short-term memory 144,the context understanding portion 112 c may bring the current positionand transmit the current position to the dialogue input manager 111 c.

When the current position is not stored in the short-term memory 144,the context understanding portion 112 c may request the current positionto the context information collection manager 112 b and the contextinformation collection manager 112 b may allow the context informationcollector 112 a to acquire the current position from the vehiclecontroller 240.

The context information collector 112 a may acquire the current positionand then store the current position in the short-term memory 144. Thecontext information collector 112 a may transmit a confirmation signalto the context information collection manager 112 b. The contextinformation collection manager 112 b may transmit the confirmationsignal to the context understanding portion 112 c and the contextunderstanding portion 112 c may bring the current position informationfrom the short-term memory 144 and then transmit the information to thedialogue input manager 111 c.

The dialogue input manager 111 c may transmit the output of the naturallanguage understanding portion 111 b and the output of the contextunderstanding portion 112 c to the dialogue manager 120 and the dialogueinput manager 111 c may manage to prevent the duplicate input fromentering to the dialogue manager 120. In this time, the output of thenatural language understanding portion 111 b and the output of thecontext understanding portion 112 c may be combined as one output andthen transmitted to the dialogue manager 120 or independentlytransmitted to the dialogue manager 120.

When the context information collection manager 112 b determines that acertain event occurs since data collected by the context informationcollector 112 a satisfies a predetermined condition, the contextinformation collection manager 112 b may transmit an action triggersignal to the context understanding portion 112 c.

The context understanding portion 112 c may search the contextunderstating table 145 for searching for context information related tothe corresponding event, and when the searched context information isnot stored in the context understating table 145, the contextunderstanding portion 112 c may transmit a context information requestsignal to the context information collection manager 112 b, again.

As illustrated in FIG. 20B, context information and the type of thecontext information related to the event may be stored in the contextunderstating table 145 according to each event.

For example, when the generated event is engine temperature warning, anengine temperature in the form of integer may be stored as the contextinformation related to the event. When the generated event is driverdrowsy driving detection, driver drowsy driving status in the form ofinteger may be stored as the context information related to the event.When the generated event is tire air pressure shortage, tire airpressure in the form of integer may be stored as the context informationrelated to the event. When the generated event is fuel warning, distanceto empty (DTE) in the form of integer may be stored as the contextinformation related to the event. When the generated event is sensorerror, sensor name in the form of text may be stored as the contextinformation related to the event.

The context information collection manager 112 b may collect the neededcontext information via the context information collector 112 a andtransmit a confirmation signal to the context understanding portion 112c. The context understanding portion 112 c may bring the needed contextinformation from the context information DB 142, the long-term memory143 or the short-term memory 144 and then transmit the contextinformation together with the action information to the dialogue inputmanager 111 c.

The dialogue input manager 111 c may input the output of the contextunderstanding portion 112 c to the dialogue manager 120.

Hereinafter a case in which the dialogue system 100 outputs apre-utterance by itself before a user's utterance is input will bedescribed.

FIG. 21 is a control block diagram illustrating a dialogue systemapplicable to a case in which the dialogue system first outputs anutterance before receiving a user's input and FIGS. 22A, 22B and 22C areviews illustrating an example of information stored in a pre-utterancecondition table.

Referring to FIG. 21, the input processor 110 of the dialogue system 100may further include a pre-utterance determiner 151 determining whetherit is a pre-utterance context, and a duplicate task processor 152. Thestorage 140 may further include a pre-utterance condition table 145 astoring pre-utterance conditions, and a task processing DB 145 b.

Data stored in the context information DB 142, the long-term memory 143,and the short-term memory 144 may be transmitted to the pre-utterancedeterminer 151. The pre-utterance determiner 151 may analyze thetransmitted data and determine whether the transmitted data satisfiesthe pre-utterance condition stored in the pre-utterance condition table145 a.

Referring to an example of FIG. 22A, in the pre-utterance conditiontable 145 a, a pre-utterance condition related to context informationand a pre-utterance message, which is output when a correspondingpre-utterance condition is satisfied, may be stored for each contextinformation.

When the context information transmitted from the context information DB142 satisfies the pre-utterance condition, the pre-utterance determiner151 may determine that it is the pre-utterance context, and generate apre-utterance trigger signal.

The pre-utterance determiner 151 may transmit the pre-utterance triggersignal to the context understanding portion 112 c with a pre-utterancemessage corresponding to the corresponding pre-utterance context.Further, the pre-utterance determiner 151 may transmit informationrelated to the corresponding pre-utterance context. The informationrelated to the corresponding pre-utterance context may include apre-utterance condition corresponding to the corresponding pre-utterancecontext or an action corresponding to the pre-utterance context,described later.

For example, when context information is related to a tire air pressureand the tire air pressure is equal to or less than a predeterminedreference value, the pre-utterance condition may be satisfied. When thepre-utterance condition of the tire air pressure is satisfied, thepre-utterance determiner 151 may determine that a pre-utterance contextis caused by the tire air pressure shortage, and generate apre-utterance trigger signal.

The pre-utterance determiner 151 may transmit the pre-utterance triggersignal with a pre-utterance message, to the context understandingportion 112 c. For example, in the pre-utterance context caused by thetire air pressure shortage, a pre-utterance message indicating that thetire air pressure is low such as “tire pressure is too low”, may betransmitted to the context understanding portion 112 c.

In addition, when context information is related to an enginetemperature and the engine temperature is equal to or higher than apredetermined reference value, the pre-utterance condition may besatisfied. When the pre-utterance condition of the engine temperature issatisfied, the pre-utterance determiner 151 may determine that apre-utterance context is caused by the abnormality in the enginetemperature, and generate a pre-utterance trigger signal.

The pre-utterance determiner 151 may transmit the pre-utterance triggersignal with a pre-utterance message, to the context understandingportion 112 c. For example, in the pre-utterance context caused by theabnormality in the engine temperature, a pre-utterance messageindicating that the engine is overheated such as “engine temperature istoo high”, may be transmitted to the context understanding portion 112c.

In addition, when context information is related to a remaining amountof gasoline and the remaining amount of gasoline is equal to or lessthan a predetermined reference value, the pre-utterance condition may besatisfied. When the user sets a destination using the navigation serviceof the vehicle, the predetermined reference value may be set based on adistance from the current position to the destination. When thedestination is not set, a default value may be applied as the referencevalue. For example, when a value smaller than a reference value forindicating a fuel shortage warning lamp, may be set as the referencevalue for the pre-utterance condition related to the remaining amount ofgasoline shortage. When the pre-utterance condition of the remainingamount of gasoline is satisfied, the pre-utterance determiner 151 maydetermine that a pre-utterance context is caused by the shortage of theremaining amount of gasoline, and generate a pre-utterance triggersignal.

The pre-utterance determiner 151 may transmit the pre-utterance triggersignal with a pre-utterance message, to the context understandingportion 112 c. For example, in the pre-utterance context caused by theshortage of the remaining amount of gasoline, a pre-utterance messageindicating that the remaining amount of gasoline is insufficient such as“the remaining amount of gasoline is not enough to the destination”, maybe transmitted to the context understanding portion 112 c.

However, the pre-utterance condition and the pre-utterance message shownin FIG. 22A are merely examples that can be applied to the dialoguesystem 100. In the above-described example, a case in which thepre-utterance message corresponding to the pre-utterance context is acontent informing the current situation has been described. However, itmay be also possible that the dialogue system 100 first suggestsexecution of a specific function or service required for thepre-utterance context.

Referring to FIG. 22B, when the pre-utterance context is caused by thetire air pressure shortage or the abnormality in the engine temperature,it may be possible to store a pre-utterance message corresponding to acontent, which proactively suggests a repair shop reservation service,such as “do you want to book the repair shop?”.

In addition, when the pre-utterance context is caused by the shortage ofremaining gasoline, it may be possible to store a pre-utterance messagecorresponding to a content, which proactively suggests a gasolinestation guidance service, such as “do you want to guide the gasolinestation?”.

In addition, when the pre-utterance context is caused by the internaltemperature of the vehicle and when the internal temperature of thevehicle is out of a predetermined reference range, a pre-utterancecondition may be satisfied. When the pre-utterance condition of theinternal temperature of the vehicle is satisfied, the contextunderstanding portion 112 c may determine that a pre-utterance contextis caused by the abnormality in the internal temperature of the vehicle,and generate a pre-utterance trigger signal.

In the pre-utterance context caused by the abnormality in the internaltemperature of the vehicle, it may be possible to store a pre-utterancemessage corresponding to a content, which proactively suggests aninternal temperature control function, such as “do you want to operatethe air conditioner?”.

In addition, when the context information is related to the microphoneinput and when a microphone input value is equal to or less than apredetermined reference value, a pre-utterance condition may besatisfied. When the pre-utterance condition of the microphone input issatisfied, the context understanding portion 112 c may determine that itis a pre-utterance context for changing the mood, and generate apre-utterance trigger signal. Accordingly, it may be possible to store apre-utterance message corresponding to a content, which proactivelysuggests a multi-media playing service, such as “do you want to play themusic?”.

In addition, when the context information is related to the open andclose of the window and whether it is raining, and when the window isopen and it is raining, the pre-utterance condition may be satisfied.When the window is open and it is raining, the context understandingportion 112 c may determine that a pre-utterance context is caused bythe open of the window, and generate a pre-utterance trigger signal.

In the pre-utterance context caused by the open of the window, it may bepossible to store a pre-utterance message corresponding to a content,which proactively suggests a window close function, such as “do you wantto close the window?”.

In the above-mentioned example of FIGS. 22A and 22B, a case in which thepre-utterance message corresponding to the pre-utterance context ispre-stored in the pre-utterance condition table 145 a has beendescribed. However, the example of the dialogue system 100 is notlimited thereto, and thus an action corresponding to the pre-utterancecontext may be pre-stored.

As mentioned above, when the user's utterance is input, the naturallanguage understanding portion 111 b may extract an action correspondingto the user's utterance with reference to the domain/action inferencerule DB 141. When the dialogue system 100 outputs the pre-utterance, anaction corresponding to the pre-utterance context may be pre-stored uponeach pre-utterance context, as illustrated in FIG. 22C.

For example, when the pre-utterance context is caused by the abnormalityin the tire air pressure and the engine temperature, “repair shopguidance” may be stored as the corresponding action, and when thepre-utterance context is caused by the lack of remaining amount ofgasoline, “gasoline station guidance” may be stored as the correspondingaction.

In addition, when the pre-utterance context is caused by the abnormalityin the internal temperature of the vehicle, “the air conditioneroperation” may be stored as the corresponding action, and when thepre-utterance context is for the change of mood, “multi-media play” maybe stored as the corresponding action. When the pre-utterance context iscaused by the open of the window, “the open and close of the window” maybe stored as the corresponding action.

As mentioned above, when the action corresponding to the pre-utterancecontext is pre-stored, the pre-utterance trigger signal with the actioncorresponding to the pre-utterance context may be transmitted to thecontext understanding portion 112 c, and the dialogue input manager 111c may input the pre-utterance trigger signal with the actioncorresponding to the pre-utterance context, to the dialogue manager 120.In this case, an operation, which is the same as a case in which theuser utterance is input, may be performed in the dialogue manager 120.

For another example, in the pre-utterance condition table 145 a, thepre-utterance context may be stored in such a manner that thepre-utterance context is matched with a virtual user utterancecorresponding to each of the pre-utterance context, and thepre-utterance determiner 151 may generate a virtual user utterancecorresponding to the pre-utterance context. The pre-utterance determiner151 may transmit the user utterance which is stored in the pre-utterancecondition table 145 a or generated by the pre-utterance determiner 151,to the natural language understanding portion 111 b in the text type.For example, when the pre-utterance context is caused by the abnormalityin the tire air pressure, a virtual user utterance, such as “check thetire pressure” or “guide to the repair shop” may be stored or generated.In addition, when the pre-utterance context is caused by the abnormalityin the internal temperature of the vehicle, a virtual user utterance,such as “turn on the air conditioner” may be stored or generated.

In addition, according to the mobile gateway method in which the mobiledevice 400 acts as a gateway between the vehicle and the dialogue system100, the dialogue system client 470 of the mobile device 400 may performsome of operations of the pre-utterance determiner 151. In this case,the dialogue system client 470 may generate a virtual user utterancecorresponding to the pre-utterance context and transmit the virtual userutterance to the natural language understanding portion 111 b.

The natural language understanding portion 111 b may extract a domainand an action corresponding to the transmitted virtual user utterance,and transmit the domain and action to the dialogue input manager 111 c.The action extracted by the natural language understanding portion 111 bmay become an action corresponding to the pre-utterance context. Aprocess, which is performed after the action corresponding to thepre-utterance context is transmitted to the dialogue manager 120, may beperformed in the same manner as the case in which the user firstlyutters.

The above-mentioned context information, pre-utterance condition,pre-utterance message, and action are merely examples applied toembodiments of the dialogue system 100, but embodiments of the dialoguesystem 100 are not limited thereto. In addition, a variety of contextinformation, pre-utterance conditions, pre-utterance messages, andactions may be stored.

When the pre-utterance determiner 151 transmits information related tothe pre-utterance trigger signal and the pre-utterance context, to thecontext understanding portion 112 c, the context understanding portion112 c may transmit the information related to the pre-utterance context,to the duplicate task processor 152.

The duplicate task processor 152 may determine whether a task, which isrelated to the pre-utterance context that currently occurs, is alreadyprocessed, or whether the task is a duplicate task.

In the task processing DB 145 b, information related to the task whichis already processed or currently processed may be stored. For example,dialogue history (including dialogue content and each dialogue time), avehicle state and whether a task is completed in the dialogue time, etc.may be stored. In addition, a result of processing and a task process,such as a route guidance using the navigation function regardless of thedialogue, may be stored.

Particularly, when the pre-utterance context is caused by the lack ofremaining amount of gasoline, the duplicate task processor 152 maydetermine whether a gasoline station guidance task is currentlyprocessed or not, based on the information stored in the task processingDB 145 b. When a dialogue for the gasoline station guidance is currentlyperformed or a gasoline station guidance action is currently performed,the duplicate task processor 152 may determine that a task related tothe current pre-utterance context, is a duplicate task, and terminatethe pre-utterance context.

Further, when an utterance for the gasoline station guidance ispreviously output and when a dialogue history in which a user rejectsthe gasoline station guidance, is present, the duplicate task processor152 may determine that a task related to the current pre-utterancecontext, is a duplicate task, and terminate the pre-utterance context.

Further, when the gasoline station guidance task using the navigationfunction is currently processed regardless of the dialogue history forthe gasoline station guidance, the duplicate task processor 152 maydetermine that a task related to the current pre-utterance context, is aduplicate task, and terminate the pre-utterance context. The duplicatetask processor 152 may recognize that the gasoline station guidance taskusing the navigation function is currently processed, based on theinformation stored in the task processing DB 145 b.

Further, when a reference period of time is not elapsed from when adialogue, which is related to the guidance of the remaining amount ofgasoline, is performed, it may be assumed that the user drives to thegasoline station by himself or herself although the gasoline stationguidance is currently not performed. Therefore, the duplicate taskprocessor 152 may determine that a task related to the currentpre-utterance context, is a duplicate task, and terminate thepre-utterance context.

Further, in a state in which a pre-utterance context is for indicating aschedule based on information, such as user's birthday or family membersbirthday, stored in the long-term memory 143, when a dialogue history,in which the same schedule is previously guided, is present and areference period of time is not elapsed from when the correspondingdialogue is performed, the duplicate task processor 152 may determinethat a task related to the current pre-utterance context, is a duplicatetask and terminate the pre-utterance context.

That is, the duplicate task processor 152 may determine whether thepre-utterance is previously output, and the user intention about thepre-utterance context, based on the dialogue history stored in the taskprocessing DB 145 b. The duplicate task processor 152 may determinewhether it is the duplicate task, based on the stored dialogue time, theuser's intention, the vehicle state or the completion of the task.

In the duplicate task processor 152, a policy configured to determinewhether it is the duplicate task, that is, whether to terminate thepre-utterance context, based on the information stored in the taskprocessing DB 145 b, may be stored. The duplicate task processor 152 maydetermine whether the task related to the current pre-utterance context,is a duplicate task, according to the stored policy, and when it isdetermined that it is the duplicate task, the duplicate task processor152 may terminate the pre-utterance context.

In the above-mentioned example, a case in which the dialogue system 100includes the pre-utterance determiner 151, the duplicate task processor152, the pre-utterance condition table 145 a and the task processing DB145 b has been described.

However, the example of the dialogue system 100 is not limited thereto,and thus it may be possible for the components shown in FIGS. 19A and19B to perform the operation of the above-mentioned components.

For example, the context understanding portion 112 c may perform theoperation of the pre-utterance determiner 151 corresponding todetermining whether to satisfy the pre-utterance condition, and theoperation of the duplicate task processor 152 corresponding toprocessing the duplicate task.

The information stored in the pre-utterance condition table 145 a may bestored in the context understating table 145 and the information storedin the task processing DB 145 b may be stored in a dialogue and actionstate DB 147 described later.

FIG. 23 is a control block diagram illustrating a configuration of adialogue manager in detail, FIG. 24 is a view illustrating an example ofinformation stored in a relational action DB, FIG. 25 is a viewillustrating an example of information stored in an action executioncondition DB, and FIG. 26 is a view illustrating an example ofinformation stored in an action parameter DB.

Referring to FIG. 23, the dialogue manager 120 may include a dialogueflow manager 121 requesting for generating, deleting and updatingdialogue or action; a dialogue action manager 122 generating, deletingand updating dialogue or action according to the request of the dialogueflow manager 121; an ambiguity solver 123 clarifying a user's intentionby resolving an ambiguity of context and an ambiguity of dialogue; aparameter manager 124 managing parameters needed for the actionexecution; an action priority determiner 125 determining whether anaction is executable about a plurality of candidate actions; and anexternal information manager 126 managing an external content list andrelated information, and managing parameter information for an externalcontent query.

The dialogue manager 120 may include a memory in which a program forperforming the above-described operation and the operation describedlater is stored, and a processor for executing the stored program. Atleast one memory and one processor may be provided, and when a pluralityof memory and processors are provided, they may be integrated on onechip or physically separated.

Each component contained in the dialogue manager 120 may be implementedby the same processor or by a separate processor.

In addition, the dialogue manager 120 and the input processor 110 may beimplemented by the same processor or by a separate processor.

When the user utterance is input or when the user utterance matched withthe pre-utterance context is transmitted to the natural languageunderstanding portion 111 b, the dialogue input manager 111 c maytransmit the result of the natural language understanding (the output ofthe natural language understanding portion) and context information (theoutput of the context understanding portion) to the dialogue flowmanager 121. In addition, when the pre-utterance context occurs, thedialogue input manager 111 c may transmit the pre-utterance triggersignal.

The output of the natural language understanding portion 111 b mayinclude information which is related to the user's utterance content,e.g., a morphological analysis result, as well as information, e.g.,domain and action. The output of the context understanding portion 112 cmay include events determined by the context information collectionmanager 112 b, as well as the context information.

The dialogue flow manager 121 may search for whether a dialogue task oran action task corresponding to the input by the dialogue input manager111 c is present in the dialogue and action state DB 147.

The dialogue and action state DB 147 may be a storage space for managingthe dialogue state and the action state, and thus the dialogue andaction state DB 147 may store currently progressing dialogue and action,and dialogue state and action state related to preliminary actions to beprocessed. For example, the dialogue and action state DB 147 may storestates related to completed dialogue and action, stopped dialogue andaction, progressing dialogue and action, and dialogue and action to beprocessed.

The dialogue and action state DB 147 may store last output state relatedto whether to switch and to nest an action, switched action index,action change time, and screen/voice/command.

For example, in a case in which the domain and the action correspondingto a user utterance is extracted, when dialogue and action correspondingto the corresponding domain and action is present in the most recentlystored dialogue, the dialogue and action state DB 147 may determine itas the dialogue task or action task corresponding to the input from thedialogue input manager 111 c.

When the domain and the action corresponding to a user utterance is notextracted, the dialogue and action state DB 147 may generate a randomtask or request that the dialogue action manager 122 refers to the mostrecently stored task.

When the dialogue task or action task corresponding to the input of theinput processor 110 is not present in the dialogue and action state DB147, the dialogue flow manager 121 may request that the dialogue actionmanager 122 generates new dialogue task or action task.

Further, when the pre-utterance trigger signal is transmitted from theinput processor 110, it may be possible to temporarily stop the dialoguetask or the action task although the dialogue task or the action task,which is currently performed, is present, and it may be possible tofirstly generate a dialogue task or an action task corresponding to thepre-utterance context. In addition, it may be possible to select thepriority according to the established rules.

When the pre-utterance trigger signal and an action corresponding to thepre-utterance trigger signal are input from the dialogue input manager111 c, the dialogue flow manager 121 may request that the dialogueaction manager 122 generates new dialogue task or action task, which isthe same manner as the case in which the action is obtained from theuser utterance.

Further, when the pre-utterance trigger signal and a pre-utterancemessage corresponding to the pre-utterance trigger signal are input fromthe dialogue input manager 111 c, the dialogue flow manager 121 mayrequest that the dialogue action manager 122 generates new dialogue taskor action task for outputting the input pre-utterance message.

When the dialogue flow manager 121 manages the dialogue flow, thedialogue flow manager 121 may refer to a dialogue policy DB 148. Thedialogue policy DB 148 may store a policy to continue the dialogue,wherein the policy may represent a policy for selecting, starting,suggesting, stopping and terminating the dialogue.

In addition, the dialogue policy DB 148 may store a point of time inwhich a system outputs a response, and a policy about a methodology. Thedialogue policy DB 148 may store a policy for generating a response bylinking multiple services and a policy for deleting previous action andreplacing the action with another action.

For example, two policies may be allowed, wherein the two polices mayinclude a policy in which a response for two actions is generated atonce, e.g., “Is it needed to perform B action after performing Aaction?” and a policy in which a separate response for another action isgenerated after a response for an action is generated, e.g., “A actionis executed”□→“Do you want to execute B action?”.

The dialogue and action state DB 147 may store a policy for determiningthe priority among the candidate actions. A priority determinationpolicy will be described later.

The dialogue action manager 122 may designate a storage space to thedialogue and action state DB 147 and generate dialogue task and actiontask corresponding to the output of the input processor 110.

When it is impossible to extract a domain and an action from the user'sutterance, the dialogue action manager 122 may generate a randomdialogue state. In this case, as mentioned later, the ambiguity solver123 may identify the user's intention based on the content of the user'sutterance, the environment condition, the vehicle state, and the userinformation, and determine an action appropriate for the user'sintention.

When the dialogue task or action task corresponding to the output of theinput processor 110 is present in the dialogue and action state DB 147,the dialogue flow manager 121 may request that the dialogue actionmanager 122 refers to the corresponding dialogue task or action task.

The action priority determiner 125 may search the relational action DB146 b to search for an action list related to the action or the eventcontained in the output of the input processor 110, and then the actionpriority determiner 125 may extract the candidate action. As illustratedin FIG. 24, the relational action DB 146 b may indicate actions relatedto each other, a relationship among the actions, an action related to anevent and a relationship among the events. For example, the routeguidance, the vehicle state check, and gasoline station recommendationmay be classified as the relational action, and a relationshipthereamong may correspond to an association.

Therefore, when executing the route guidance, the vehicle state checkand gasoline station recommendation may be performed together. In thiscase, “performing together” may include a case in which the vehiclestate check and gasoline station recommendation are performed before orafter the route guidance and a case in which the vehicle state check andgasoline station recommendation are performed during the route guidance(e.g., adding as a stopover).

A warning light output event may be stored as an event-action related toa repair shop guidance action and a relationship therebetween maycorrespond to an association.

When the warning light output event occurs, the repair shop guidanceaction may be performed according to the warning light type or whetherto need the repair.

When the input processor 110 transmit an action corresponding to theuser's utterance together with an event determined by the contextinformation collection manager 112 b, an action related to the actioncorresponding to the user's utterance and an action related to the eventmay become a candidate action.

The extracted candidate action list may be transmitted to the dialogueaction manager 122 and the dialogue action manager 122 may update theaction state of the dialogue and action state DB 147 by adding thecandidate action list.

The action priority determiner 125 may search for conditions to executeeach candidate action in an action execution condition DB 146 c.

As illustrated in FIG. 25, the action execution condition DB 146 c maystore conditions, which are needed for performing the action, andparameters, which are to determine whether to meet the correspondingcondition, according to each action.

For example, an execution condition for the vehicle state check may be acase in which a destination distance is equal to or greater than 100 km,wherein a parameter for determining the condition may correspond to thedestination distance. A condition for the gasoline stationrecommendation may be a case in which a destination distance is greaterthan a distance to empty (DTE), wherein a parameter for determining thecondition may correspond to the destination distance and the distance toempty (DTE).

The action priority determiner 125 may transmit the execution conditionof the candidate action to the dialogue action manager 122 and thedialogue action manager 122 may add the execution condition according toeach candidate action and update the action state of the dialogue andaction state DB 147.

The action priority determiner 125 may search for a parameter that isneeded to determine an action execution condition (hereinafter refer tocondition determination parameter), from the context information DB 142,the long-term memory 143, the short-term memory 144 or the dialogue andaction state DB 147, and determine whether it is possible to execute thecandidate action, using the searched parameter.

When a parameter used to determine an action execution condition is notstored in the context information DB 142, the long-term memory 143, theshort-term memory 144 or the dialogue and action state DB 147, theaction priority determiner 125 may bring the needed parameter from theexternal content server 300 via the external information manager 126.

The action priority determiner 125 may determine whether it is possibleto perform the candidate action using the parameter used to determine anaction execution condition. In addition, the action priority determiner125 may determine the priority of the candidate action based on whetherto perform the candidate action and priority determination rules storedin the dialogue policy DB 148.

A score for each candidate action may be calculated according to thecurrent situation. A higher priority may be given to a candidate actionhaving more of calculated score. For example, an action corresponding tothe user's utterance, a safety score, a convenience score, a processingtime, a processing point of time (whether to immediately process ornot), a user preference (the user's reception level when suggesting aservice or a preference pre-determined by a user), an administratorscore, a score related to vehicle state, and an action success rate(dialogue success rate) may be used as a parameter for calculating thescore, as illustrated in the following equation 1. w1, w2, w3, w4, w5,w6, w7, w8, and w9 represent a weight value for each parameter.Priority score=w1*user utterance action+w2*safety score+w3*conveniencescore+w4*processing time+w5*processing point of time+w6*userpreference+w7*administrator score+w8*score related to vehiclestate+w9*action success rate*possibility of action execution (1:possible, not yet known, 0: impossible)*action completion status(completion: 1, incompletion: 0).  [Equation 1]

As mentioned above, the action priority determiner 125 may provide themost needed service to a user by searching for an action directlyconnected to the user's utterance and context information and an actionlist related thereto, and by determining a priority therebetween.

The action priority determiner 125 may transmit the possibility of thecandidate action execution and the priority to the dialogue actionmanager 122 and the dialogue action manager 122 may update the actionstate of the dialogue and action state DB 147 by adding the transmittedinformation.

The parameter manager 124 may search for a parameter used to performeach candidate action (hereinafter refer to action parameter) in anaction parameter DB 146 a.

As illustrated in FIG. 26, the action parameter DB 146 a may store anecessary parameter, an alternative parameter, an initial value ofparameter and a reference position for bring the parameter, according toeach action. In a state in which the initial value of parameter isstored, when a parameter value corresponding to the correspondingparameter is not present in the user's utterance and the contextinformation output from the input processor 110 and when the parametervalue is not present in the context information DB 142, it may bepossible to perform an action according to the stored initial value orit may be possible to confirm whether to perform an action according tothe stored initial value, to a user.

For example, the necessary parameter used for the route guidance mayinclude the current position and the destination, and the alternativeparameter may include the type of route. An initial value of thealternative parameter may be stored as a fast route. The currentposition and the destination may be acquired by searching the dialogueand action state DB 147, the context information DB 142, the short-termmemory 144 or the long-term memory 143 in an order.

The necessary parameter used for the vehicle state check may includevehicle state information, and the alternative parameter may include apart to be examined (hereinafter referred as “check part”). An entirepart may be stored as an initial value of the alternative parameter. Thevehicle state information may be acquired from the context informationDB 142.

The alternative parameter for the gasoline station recommendation mayinclude a favorite gasoline station, and “A oil” may be stored as aninitial value of the alternative parameter. The favorite gasolinestation may be acquired from the long-term memory 143. The alternativeparameter may further include the fuel type of the vehicle, and the fuelprice.

As mentioned above, the parameter manager 124 may bring the parametervalue of the parameter searched in the action parameter DB 146 a, fromthe corresponding reference position. The reference position from whichthe parameter value is brought may be at least one of the contextinformation DB 142, the short-term memory 144 or the long-term memory143, the dialogue and action state DB 147, and the external contentserver 300.

The parameter manager 124 may bring the parameter value from the 300 viathe external information manager 126. The external information manager126 may determine from which information is brought, by referring to theexternal service aggregate DB 146 d.

The external service aggregate DB 146 d may store information related tothe external content server connected to the dialogue system 100. Forexample, the external service aggregate DB 146 d may store externalservice name, explanation about an external service, the type ofinformation provided from an external service, external service usingmethod, and a subject of providing the external service.

The initial value acquired by the parameter manager 124 may betransmitted to the dialogue action manager 122 and the dialogue actionmanager 122 may update the dialogue and action state DB 147 by addingthe initial value according to the candidate action to the action state.

The parameter manager 124 may acquire initial values of all of thecandidate actions or the parameter manager 124 may acquire only initialvalues of the candidate actions which are determined to be executable bythe action priority determiner 125.

The parameter manager 124 may selectively use an initial value among adifferent type of initial values indicating the same information. Forexample, “Seoul station” indicating the destination and which is in theform of text may be converted into “Seoul station” in the form of POI,by using a destination search service by the navigation system.

When the ambiguity is not present in the dialogue and the context, itmay be possible to acquire the needed information and to manage thedialogue and action according to the above mentioned operation of theaction priority determiner 125, the parameter manager 124 and theexternal information manager 126. When the ambiguity is present in thedialogue and the context, it may be difficult to provide a serviceneeded for the user using only an operation of the action prioritydeterminer 125, the parameter manager 124 and the external informationmanager 126.

In this case, the ambiguity solver 123 may deal with the ambiguity inthe dialogue or in the context. For example, when anaphora, e.g., theperson, that place on yesterday, father, mother, grandmother, anddaughter-in-law, is contained in the dialogue, there may be ambiguitybecause it is not clear that the anaphora represents whom or which. Inthis case, the ambiguity solver 123 may resolve the ambiguity byreferring to the context information DB 142, the long-term memory 143 orthe short-term memory 144 or provide a guidance to resolve theambiguity.

For example, an ambiguous word contained in “that place on yesterday”,“the market near the house”, and “Seoul station I went yesterday” maycorrespond to a parameter value of the action parameter or a parametervalue of the condition determination parameter. However, in this case,it is impossible to perform a real action or to determine an actionexecution condition by using the corresponding word, due to theambiguity of the word.

The ambiguity solver 123 may resolve the ambiguity of the initial valueby referring to the information stored in the context information DB142, the long-term memory 143 or the short-term memory 144. As needed,the ambiguity solver 123 may bring the needed information from theexternal content server 300 by using the external information manager126.

For example, the ambiguity solver 123 may search for a place where auser went yesterday by referring to the short-term memory 144, so as toconvert “that place on yesterday” into information that is available asa destination for the route guidance action. The ambiguity solver 123may search for a user's house address by referring to the long-termmemory 143 and bring location information related to A market near theuser's house address, from the external content server 300. Therefore,the ambiguity solver 123 may convert “A market near house” intoinformation that is available as a destination for the route guidanceaction.

When an action (object and operator) is not clearly extracted by theinput processor 110 or when the user' intention is not clear, theambiguity solver 123 may identify the user's intention by referring toan ambiguity resolution information DB 146 e, and determine an actioncorresponding to the identified intention.

FIG. 27 is a table illustrating an example of information stored in theambiguity resolution information DB.

Based on the vehicle state information and the surrounding environmentinformation, the ambiguity resolution information DB 146 e may match anutterance with an action corresponding to the utterance and then storethe utterance and the action. The utterance stored in the ambiguityresolution information DB 146 e may be an utterance in which an actioncannot be extracted by the natural language understanding. FIG. 27illustrates a case in which an utterance's content according to themorphological analysis result is that hands are freezing or hands arecold.

The surrounding environment information may include the outsidetemperature of the vehicle and whether it is raining, and the vehiclestate information may include ON/OFF of air conditioner and heater andwind volume and wind direction of the air conditioner, and ON/OFF of thesteering wheel heating wire.

Particularly, in a state in which the outside temperature is more than20 degree while it is raining, when the air conditioner is turned on(ON), it may be identified that an air conditioner temperature is set tobe low and thus “increasing an air conditioner temperature by 3 degree”may be stored as a vehicle control action corresponding thereto.

In a state in which the outside temperature is more than 20 degree whileit is raining, when the air conditioner is turned off (OFF), it may beidentified that the user feels the cold due to the rain, and thus“heater ON” may be stored as a vehicle control action correspondingthereto.

In a state in which the outside temperature is more than 20 degree whileit is not raining, when the air conditioner is turned on (ON) and thewind direction of the air conditioner is an upside, it may be identifiedthat hands are freezing since the wind of the air condition directlyaffects to the hands, and thus “changing the wind direction of the airconditioner to the down side” may be stored as a vehicle control actioncorresponding thereto.

In a state in which the outside temperature is more than 20 degree whileit is not raining, when the air conditioner is turned on (ON), the winddirection of the air conditioner is the down side and the wind volume isset to be more than a middle level, it may be identified that a userfeels the cold due to an excessively strong wind volume of the airconditioner, and thus “lowering the wind volume of the air conditioner”may be stored as a vehicle control action corresponding thereto.

In a state in which the outside temperature is more than 20 degree whileit is not raining, when the air conditioner is turned on (ON), the winddirection of the air conditioner is the down side and the wind volume isset to be weak, “increasing an air conditioner temperature by 3 degree”may be stored as a vehicle control action corresponding thereto.

In a state in which the outside temperature is lower than 20 degree,when the heater is turned off (OFF), it may be identified that hands arefreezing due to the cold weather, and thus “turning on heater” may bestored as a vehicle control action corresponding thereto.

In a state in which the outside temperature is lower than 20 degree,when the heater is turned on (ON) and the steering wheel heating wire isturned off, it may be identified that hands are freezing since hot airis not transmitted to the hands, and thus “steering wheel heating wireON” may be stored as a vehicle control action corresponding thereto.

In a state in which the outside temperature is lower than 20 degree,when the heater and the steering wheel heating wire are turned on (ON)and the wind direction of the heater is the down side, it may beidentified that hands are freezing since the wind of the heater is nottransmitted to the hands, and thus “changing the wind direction of theheater to the bi-directions” may be stored as a vehicle control actioncorresponding thereto.

In a state in which the outside temperature is lower than 20 degree, theheater and the steering wheel heating wire are turned on (ON), the winddirection of the heater is the up side, when a heater temperature is setto be lower than the highest, “increasing the temperature of the heater”may be stored as a vehicle control action corresponding thereto.

In a state in which the outside temperature is lower than 20 degree, theheater and the steering wheel heating wire are turned on (ON), the winddirection of the heater is the up side, and the heater temperature isset to be the highest, when the volume of the heater is not set to bethe highest, “increasing the wind volume of the heater” may be stored asa vehicle control action corresponding thereto.

In a state in which the outside temperature is lower than 20 degree, theheater and the steering wheel heating wire are turned on (ON), the winddirection of the heater is the up side, and a heater temperature and thewind volume of the heater are set to be the highest, when the seat heatline is turned off, “turning on the seat heat line” may be stored as avehicle control action corresponding thereto.

In a state in which the outside temperature is lower than 20 degree, theheater and the steering wheel heating wire are turned on (ON), the winddirection of the heater is the up side, and the heater temperature andthe wind volume of the heater are set to be the highest, when the seatheat line is turned on, “informing that wait for a while because heateris in full operation now” may be stored as a vehicle control actioncorresponding thereto.

FIGS. 28A and 28B are tables illustrating a variety of examples in whichthe vehicle control is performed since the ambiguity solver resolves theambiguity by referring to the ambiguity resolution information DB andextracting an action.

For example, as illustrated in FIGS. 28A and 28B, in a state in which anutterance's content according to the morphological analysis result isthat hands are freezing or hands are cold, when the surroundingenvironment is summer, the vehicle state is that the wind direction ofthe air conditioner is an upper side (upside) of the passenger's head,an air conditioner set temperature is 19 degree, and the wind volume ofthe air conditioner is a high level, it may be identified that hands arefreezing since the wind of the air conditioner is directed to the hands.An air conditioner control action for lowering the wind volume strengthwhile changing the wind direction to the foot side (downside) may beextracted as an action corresponding to the utterance and it may bepossible to control the vehicle according to the extracted action.

In the utterance having the same content, when the surroundingenvironment is winter, the vehicle state is that the wind direction ofthe air conditioner is the passenger's feet, an air conditioner settemperature is 25 degree, and the wind volume of the air conditioner isa high level, it may be identified that hands are freezing since hot airis not transmitted to the hands. “Turning on steering wheel heat line”action may be extracted as an action corresponding to the utterance andit may be possible to control the vehicle according to the extractedaction.

In a state in which an utterance's content according to themorphological analysis result is “stuffiness”, when a vehicle speed is30 km or less and a front and rear clearance is less than 30 cm, it maybe identified that stuffiness is caused by the heavy traffic. Therefore,“changing a route option (fast route guidance) in the route guidanceaction”, “playing a multi content, e.g., music”, or “turning on chattingfunction” may be extracted as an action corresponding to the utteranceand it may be possible to control the vehicle according to the extractedaction.

In a state in which an utterance's content according to themorphological analysis result is “drowsiness”, when the vehicle state isan internal air mode, it may be identified that the drowsiness is causedby the lack of air circulation. Therefore, “changing into an externalair mode” may be extracted as an action corresponding to the utteranceand it may be possible to control the vehicle according to the extractedaction.

In the utterance having the same content, when the vehicle state is theexternal air mode and the heater is turned on (ON), it may be identifiedthat the drowsiness is caused by the hot air emitted from the heater.“Opening window” may be extracted as an action corresponding to theutterance and it may be possible to control the vehicle according to theextracted action.

In a state in which an utterance's content according to themorphological analysis result is “sweating” or “hot”, when thesurrounding environment is winter and the heater is turned on (ON), itmay be identified that the heat is caused by the hot air emitted fromthe heater. Therefore, “lowering the heater temperature” or “reducingthe wind volume” may be stored as an action corresponding to theutterance.

In the utterance having the same content, when the surroundingenvironment is winter and when the heater is turned off (OFF), it may beidentified that the heat is caused by the user' body heat. Therefore,“opening the window” or “suggesting opening the window” may be extractedas an action corresponding to the utterance and it may be possible tocontrol the vehicle according to the extracted action.

In the utterance having the same content, when the surroundingenvironment is summer and when the air conditioner is turned off (OFF),it may be identified that the heat is caused by increased internaltemperature of the vehicle. Therefore, “turning on the air conditioner”may be extracted as an action corresponding to the utterance and it maybe possible to control the vehicle according to the extracted action.

In the utterance having the same content, when the surroundingenvironment is summer and when the air conditioner is turned on (ON), itmay be identified that the heat is caused by the air conditionertemperature set to be high. Therefore, “lowering the air conditionertemperature” or “increasing the wind volume of the air conditioner” maybe extracted as an action corresponding to the utterance and it may bepossible to control the vehicle according to the extracted action.

In a state in which an utterance's content according to themorphological analysis result is “cold”, when the surroundingenvironment is summer and when the air conditioner is turned on (ON), itmay be identified that the cold is caused by the air conditionertemperature set to be excessively low or by the excessively strong windof the air conditioner. Therefore, “increasing the air conditionertemperature” or “reducing the wind volume” may be extracted as an actioncorresponding to the utterance and it may be possible to control thevehicle according to the extracted action.

In the utterance having the same content, when the surroundingenvironment is summer and when the air conditioner is turned off (OFF),it may be identified that the cold is caused by the user's bodycondition. “Operating the heater” or “checking user's biorhythm” may beextracted as an action corresponding to the utterance and it may bepossible to control the vehicle according to the extracted action.

In the utterance having the same content, when the surroundingenvironment is winter and the heater is turned on (ON), it may beidentified that the cold is caused by the heater temperature set to below or the weak wind volume. Therefore, “increasing the heatertemperature” or “increasing the wind volume” may be extracted as anaction corresponding to the utterance and it may be possible to controlthe vehicle according to the extracted action.

In the utterance having the same content, when the surroundingenvironment is winter and the heater is turned off (OFF), it may beidentified that the cold is caused by the non-operation of the heater.“Operating the heater” may be extracted as an action corresponding tothe utterance and it may be possible to control the vehicle according tothe extracted action.

In a state in which an utterance's content according to themorphological analysis result is “head hurts”, when the surroundingenvironment is winter and the heater is turned on (ON), it may beidentified that the headache is caused by the lack of the aircirculation. Therefore, “changing into an external air mode” or “openingthe window” may be extracted as an action corresponding to the utteranceand it may be possible to control the vehicle according to the extractedaction.

In the utterance having the same content, when the surroundingenvironment is winter and the heater is turned off (OFF), it may beidentified that the headache is caused by the cold. “Operating theheater” may be extracted as an action corresponding to the utterance andit may be possible to control the vehicle according to the extractedaction.

In the utterance having the same content, when the surroundingenvironment is summer and the air conditioner is turned off (OFF), itmay be identified that the headache is caused by the heat. “Operatingthe air conditioner” may be extracted as an action corresponding to theutterance and it may be possible to control the vehicle according to theextracted action.

In the utterance having the same content, when the surroundingenvironment is summer and the air conditioner is turned on (ON), it maybe identified that the headache is caused by the air-conditioningitis.“Changing the wind direction or the wind volume of the air conditioner”may be extracted as an action corresponding to the utterance and it maybe possible to control the vehicle according to the extracted action.

In a state in which an utterance's content according to themorphological analysis result is “uncomfortable”, when the surroundingenvironment is winter and it is raining, it may be identified that theuncomfortableness is caused by the high humidity. Therefore, “operatingdefogging function” or “operating dehumidifying function” may beextracted as an action corresponding to the utterance and it may bepossible to control the vehicle according to the extracted action.

In the utterance having the same content, when the surroundingenvironment is summer and it is not raining, it may be identified thatthe uncomfortableness is caused by the seasonal characteristics and theheat. Therefore, “operating the air conditioner at the lowesttemperature” may be extracted as an action corresponding to theutterance and it may be possible to control the vehicle according to theextracted action.

In the utterance having the same content, when the surroundingenvironment is summer and it is raining, it may be identified that theuncomfortableness is caused by the heat and the high humidity.Therefore, “operating the air conditioner at the dehumidifying mode” maybe extracted as an action corresponding to the utterance and it may bepossible to control the vehicle according to the extracted action.

According to the operation of the ambiguity solver 123 described above,although there is the ambiguity in the user's utterance or situation,the ambiguity solver 123 may precisely identify an action that isactually desired by a user, or an action that is actually needed for auser, and provide the desired action and the needed action by integrallyconsidering the surrounding environment information and the vehiclestate information with the user's utterance.

The information related to the action determined by the ambiguity solver123 may be transmitted to the dialogue action manager 122 and thedialogue action manager 122 may update the dialogue and action state DB147 based on the transmitted information.

As mentioned above, the action priority determiner 125 and the parametermanager 124 may determine an action execution condition about the actiondetermined by the ambiguity solver 123, determine the priority thereofand bring the parameter value.

When all of values are acquired wherein the values are acquired by thecurrent context and dialogue, among parameter values used to executeeach action, the dialogue action manager 122 may transmit a signal tothe dialogue flow manager 121.

When the necessary parameter value for the action execution and thecondition determination is acquired through the user since the necessaryparameter is not present in the dialogue and action state DB 147, theexternal content server 300, the long-term memory 143, the short-termmemory 144 and the context information DB 142, the result processor 130may generate a dialogue response for asking parameter values to theuser.

The dialogue flow manager 121 may transmit information and dialoguestate related to an action corresponding to the first priority action tothe result processor 130. In addition, the dialogue flow manager 121 maytransmit the information related to the plurality of candidate actions,according to the dialogue policy.

When the dialogue system 100 outputs the pre-utterance, that is thepre-utterance trigger signal is generated by the input processor 110,the dialogue state transmitted from the result processor 130 may includethe pre-utterance trigger signal. However, it is not required that thepre-utterance trigger signal is contained in the dialogue state, but anytype of information may be contained in the dialogue state as long asindicating the pre-utterance context. When the information indicatingthe pre-utterance context is contained in the dialogue state, the resultprocessor 130 may firstly output a dialogue response over than othertype response, or output the dialogue response together with other typeresponse.

In a state in which the dialogue system 100 outputs the pre-utterance,when a pre-utterance message corresponding to the pre-utterance contextis input from the dialogue input manager 111 c, it may be possible totransmit the pre-utterance message to the result processor 130 withoutthe above-mentioned process of the ambiguity solution, the parametermanagement, and the action priority determination.

In a state in which the dialogue system 100 outputs the pre-utterance,when an action corresponding to the pre-utterance context is input fromthe dialogue input manager 111 c, it may be possible to transmit thepre-utterance message to the result processor 130 with or without theabove-mentioned process of the ambiguity solution, the parametermanagement, and the action priority determination.

FIG. 29 is a control block diagram illustrating a configuration of theresult processor in details.

Referring to FIG. 29, the result processor 130 may include a responsegeneration manager 131 managing generation of a response needed forexecuting an action input from the dialogue manager 120; a dialogueresponse generator 132 generating a response in text, image or audiotype according to the request of the response generation manager 131; acommand generator 136 generating a command for the vehicle control orthe provision of service using an external content according to arequest of the response generation manager 131; a service editor 134sequentially or sporadically executing a plurality of service andcollection a result thereof to provide a service desired by a user; anoutput manager 133 outputting the generated text type response, imagetype response, or audio type response, outputting the command generatedby the command generator 136, or determining an order of the output whenthe output is plural; and a memory manager 135 managing the long-termmemory 143 and the short-term memory 144 based on the output of theresponse generation manager 131 and the output manager 133.

The result processor 130 may include a memory in which a program forperforming the above-described operation and the operation describedlater is stored, and a processor for executing the stored program. Atleast one memory and one processor may be provided, and when a pluralityof memory and processors are provided, they may be integrated on asingle chip or physically separated.

Each component contained in the result processor 130 may be implementedby the same processor or by a separate processor.

In addition, the result processor 130, the dialogue manager 120 and theinput processor 110 may be implemented by the same processor or by aseparate processor.

The response that is output by corresponding to the user's utterance orcontext may include the dialogue response, the vehicle control, and theexternal content provision. The dialogue response may include an initialdialogue, a question, and an answer including information. The dialogueresponse may be stored as database in a response template 149.

The response generation manager 131 may request that the dialogueresponse generator 132 and the command generator 136 generate a responsethat is needed to execute an action, which is determined by the dialoguemanager 120. For this, the response generation manager 131 may transmitinformation related to the action to be executed, to the dialogueresponse generator 132 and the command generator 136, wherein theinformation related to the action to be executed may include an actionname and a parameter value. When generating a response, the dialogueresponse generator 132 and the command generator 136 may refer to thecurrent dialogue state and action state.

The dialogue response generator 132 may extract a dialogue responsetemplate by searching the response template 149, and generate thedialogue response by filling the extracted dialogue response templatewith the parameter value. The generated dialogue response may betransmitted to the response generation manager 131. When the parametervalue needed to generate the dialogue response is not transmitted fromthe dialogue manager 120 or when an introduction of using the externalcontent is transmitted, the dialogue response generator 132 may receivethe parameter value from the external content server 300 or search thelong-term memory 143, the short-term memory 144 or the contextinformation DB 142.

For example, when the action determined by the dialogue manager 120corresponds to the route guidance, the dialogue response generator 132may search the response template 149 and then extract a dialogueresponse template “[duration:-] will be taken from [current position:-]to [destination:-]. Start the guidance?”

[Current position] and [destination] among parameters which are neededto be filled, in the dialogue response template may be transmitted fromthe dialogue manager 120, and a parameter value for [duration] may benot transmitted. In this case, the dialogue response generator 132 mayrequest a duration that is taken from [current position] to[destination], to the external content server 300.

When the response to the user utterance or context includes the vehiclecontrol or the external content provision, the command generator 136 maygenerate a command to execute the vehicle control or the externalcontent provision. For example, when the action determined by thedialogue manager 120 is the control of the air conditioning device,window and AVN, the command generator 136 may generate a command toexecute the control and then transmit the command to the responsegeneration manager 131.

When the action determined by the dialogue manager 120 needs theexternal content provision, the command generator 136 may generate acommand to receive the corresponding content from the external contentserver 300 and then transmit the command to the response generationmanager 131.

When a plurality of commands is provided by the command generator 136,the service editor 134 may determine a method and an order to executethe plurality of commands and transmit the method and order to theresponse generation manager 131.

The response generation manager 131 may transmit the response, which istransmitted from the dialogue response generator 132, the commandgenerator 136, or the service editor 134, to the output manager 133.

The output manager 133 may determine an output timing, an outputsequence and an output position of the dialogue response generated bythe dialogue response generator 132 and the command generated by thecommand generator 136.

The output manager 133 may output a response by transmitting thedialogue response generated by the dialogue response generator 132 andthe command generated by the command generator 136 to an appropriateoutput position at an appropriate order with an appropriate timing. Theoutput manager 133 may output Text to speech (TTS) response via thespeaker 232 and a text response via the display 231. When outputting thedialogue response in the TTS type, the output manager 133 may use a TTSmodule provided in the vehicle 200 or alternatively the output manager133 may include a TTS module.

According to the control target, the command may be transmitted to thevehicle controller 240 or the communication device 280 for communicatingwith the external content server 300.

The response generation manager 131 may also transmit the responsetransmitted from the dialogue response generator 132, the commandgenerator 136, or the service editor 134, to the memory manager 135.

The output manager 133 may transmit a response that is output by itself,to the memory manager 135.

The memory manager 135 may manage the long-term memory 143 or theshort-term memory 144 based on the content transmitted from the responsegeneration manager 131 and the output manager 133. For example, thememory manager 135 may update the short-term memory 144 by storing thedialogue content between the user and the system, based on the generatedand output dialogue response. The memory manager 135 may update thelong-term memory 143 by storing information related to the user that isacquired by the dialogue with the user.

In the information stored in the short-term memory 144, the persistentinformation, e.g., user's preference or orientation, or informationwhich is used to acquire the persistent information, may be stored inthe long-term memory 143.

Based on the vehicle control and the external content requestcorresponding to the generated and output command, the user preferenceor the vehicle control history stored in the long-term memory 143 may beupdated.

Meanwhile, in a state in which the dialogue system 100 outputs thepre-utterance before the user inputs the utterance, when the actioncorresponding to the pre-utterance context is input from the dialogueinput manager 111 c, the dialogue response generator 132 receivinginformation related to an action may extract a dialogue responsetemplate by searching the response template 149, and generate thedialogue response by filling the extracted dialogue response templatewith the parameter value. The generated dialogue response may betransmitted to the response generation manager 131. The dialogueresponse may become the pre-utterance of the dialogue system 100.

The response generation manager 131 may transmit the dialogue responsetransmitted from the dialogue response generator 132, to the outputmanager 133.

The output manager 133 may output the dialogue response generated by thedialogue response generator 132 via the speaker 232.

When the result processor 130 receives the pre-utterance message as itis, corresponding to the pre-utterance context, from the dialogue flowmanager 121, the input pre-utterance message may become the dialogueresponse and the input pre-utterance message may be transmitted to theoutput manager 133.

The output manager 133 may output the transmitted pre-utterance messagevia the speaker 232.

When the user utterance is input after the dialogue system 100 outputsthe pre-utterance, the operation that is the same as the operation forprocessing the user utterance may be performed.

According to the above mentioned embodiment, the dialogue system 100 mayprovide a service which is the most appropriate for a user, byconsidering a variety of situations occurring inside of the vehicle.Without inputting the user's utterance, the dialogue system 100 maydetermine a service needed for a user by itself based on the contextinformation or the driver information, which is collected by itself, andproactively provide the service.

For example, evaluation criteria for the vehicle state may be variableaccording to the situation when starting the vehicle, and thus it may bepossible to proactively provide a feed-back. A driving start time may bedefined as a vehicle starting time, a point of time when releasing anelectronic parking brake (EPB) or a point of time when setting anavigation destination. A vehicle condition evaluation systemcalculating a driving available score may give a weight to an individualdevice, and change a variable weight applied to the individual device,according to the situation factors. When it is determined that there isproblems in the vehicle state, it may be possible to provide a solutionabout the individual device, e.g., a repair shop guidance.

It may be possible to determine whether the vehicle is lack of fuel ornot by considering the destination when the vehicle starting. When thelack of fuel, it may be possible to perform adding a user's favoritegasoline station to an automatic stopover in the route to thedestination, as a feedback of the lack of fuel, and to inform the userthe change in the stopover. In addition, according to the user'sresponse, the gasoline station which is added as the automatic stopovermay be changed.

Although the current vehicle state does not indicate the lack of fuel,it may be possible to proactively provide a gasoline station or arefueling time by comprehensively considering a user's next schedule, amajor moving record and an amount of remaining fuel.

By acquiring information related to driver's body condition and sleepingrecord, it may be possible to conditionally permit a vehicle startingbased on the acquired information. For example, when recognizing therisk of the drowsy driving by recognizing the body conditions and thesleeping record in the outside of the vehicle, it may be possible torecommend that a user does not drive the vehicle. Alternatively, it maybe possible to provide information related to a recommended driving timeaccording to the body conditions or the sleeping record.

When a trigger indicating the risk of the drowsy driving occurs,repeatedly, it may be possible to detect the risk of the drowsy drivingand output the warning according to the degree of the risk or to providea feedback such as automatically changing the route, i.e., changing theroute to a rest area. The trigger indicating the risk of the drowsydriving may be acquired by manually measuring the driver's state and thevehicle state, e.g., a case in which a hear rate is reduced, a case inwhich a front and rear clearance is a reference distance or more, a casein which the vehicle speed is a reference speed or less, or by activemeasurement via the dialogue, e.g., a case of uttering a question to adriver and measuring a driver's response speed to the question.

When a user inputs an utterance indication an emotion, the dialoguesystem 100 may not extract a certain domain or an action from the user'sutterance. However, the dialogue system 100 may identity the user'sintention by using the surrounding environment information, the vehiclestate information and the user state information, and then continue thedialogue. As mentioned above, the embodiment may be performed byresolving the ambiguity of the user's utterance through the ambiguitysolver 123.

Hereinafter an example of dialogue processing using the dialogue system100 will be described in details.

FIGS. 30 to 42 are views illustrating a particular example in which thedialogue system 100 processes an input, manages a dialogue, and outputsa result when a user inputs an utterance related to a route guidance.

As illustrated in FIG. 30, when a user input an utterance “let's go toSeoul station we went yesterday” the speech recognizer 111 a may outputthe user's speech as the utterance in the text form (let's go to Seoulstation we went yesterday).

The natural language understanding portion 111 b may perform themorphological analysis and output [domain: navigation], [action: routeguidance], [speech act; request], and [parameter: NLU: destination:Seoul station] from a morphological analysis result (yesterday/NNG,went/VV, Seoul station/NNP, go/VV), by referring to the domain/actioninference rule DB 141 and then input them to the dialogue input manager111 c.

Referring to FIG. 31, while transmitting the natural languageunderstanding result of the natural language understanding portion 111 bto the context understanding portion 112 c, the dialogue input manager111 c may request that the context understanding portion 112 c sendadditional information when additional information is present in thecontext understanding portion 112 c.

The context understanding portion 112 c may search the contextunderstating table 145 and extract a fact that context informationrelated to [domain: navigation] and [action: route guidance], is thecurrent position” and the type of the context information is GPS value.

The context understanding portion 112 c may extract a GPS value of thecurrent position by searching the context information DB 142. When theGPS value of the current position is not stored in the contextinformation DB 142, the context understanding portion 112 c may requestthe GPS value of the current position to the context informationcollection manager 112 b.

The context information collection manager 112 b may transmit a signalto the context information collector 112 a so that the contextinformation collector 112 a collects the GPS value of the currentposition. The context information collector 112 a may collect the GPSvalue of the current position from the vehicle controller 240 and thenstore the GPS value of the current position in the context informationDB 142 while sending a GPS value collection confirmation signal to thecontext information collection manager 112 b. When the contextinformation collection manager 112 b transmits the GPS value collectionconfirmation signal to the context understanding portion 112 c, thecontext understanding portion 112 c may extract the GPS value of thecurrent position from the context information DB 142 and then transmitthe GPS value of the current position to the dialogue input manager 111c.

The dialogue input manager 111 c may combine [domain: navigation],[action: route guidance], [speech act; request], [parameter: NLU:destination: Seoul station] and [context information: current position:Uiwang station (GPS value)] which are the natural language understandingresult and then transmit the combined information to the dialoguemanager 120.

Referring to FIG. 32, the dialogue flow manager 121 may search thedialogue and action state DB 147 and determine whether dialogue task oraction task, which is currently progressing, is present. In this time,the dialogue flow manager 121 may refer to the dialogue policy DB 148.According to the embodiment, it is assumed that dialogue task or actiontask, which is currently progressing, is not present.

The dialogue flow manager 121 may request that the dialogue actionmanager 122 generate an action task and dialogue task corresponding tothe output of the input processor 110. The generation of the action taskand dialogue task may represent designating a storage space for storingand managing the information related to the action state and thedialogue state.

Therefore, the dialogue action manager 122 may designate the storagespace in the dialogue and action state DB 147 to store the informationrelated to the action state and the dialogue state.

The dialogue action manager 122 may transmit the action state and thedialogue state to the action priority determiner 125.

The action priority determiner 125 may search for the vehicle statecheck and the gasoline station recommendation which are related to theroute guidance, in the relational action DB 146 b. The route guidanceaction and the relational action may become candidate actions.

The action priority determiner 125 may determine the priority of thecandidate actions according to the pre-stored rules. Before theexecution condition of the candidate action is determined, the prioritymay be determined or alternatively after the execution condition of thecandidate action is determined, the priority may be determined aboutonly candidate action which satisfies the execution condition.

The candidate action list may be transmitted to the dialogue actionmanager 122, again, and the dialogue action manager 122 may update theaction state by adding the searched relational actions.

Referring to FIG. 33, the action priority determiner 125 may search foran execution condition about each candidate action or parameters todetermine the execution condition in the action execution condition DB146 c. The action priority determiner 125 may also determine thepriority among the candidate actions.

For example, a condition for the vehicle state check may be a case inwhich a destination distance is equal to or greater than 100 km, whereina parameter for determining the condition may correspond to thedestination distance.

A condition for the gasoline station recommendation may be a case inwhich a destination distance is greater than a distance to empty (DTE),wherein a parameter for determining the condition may correspond to thedestination distance and the distance to empty (DTE).

The dialogue action manager 122 may update the action state by addingthe condition for executing the each candidate action and a parameterneeded to determine the condition, to the dialogue and action state DB147.

The action priority determiner 125 may search for a parameter value thatis needed to determine whether the candidate action satisfies theexecution condition or not, in the dialogue and action state DB 147, thecontext information DB 142, the long-term memory 143, or the short-termmemory 144 and bring the parameter value from the dialogue and actionstate DB 147, the context information DB 142, the long-term memory 143,or the short-term memory 144.

When the parameter value is contained in the previous dialogue content,in the context information related to the dialogue content, or in thecontext information related to the generated event, the action prioritydeterminer 125 may bring the parameter value from the dialogue andaction state DB 147.

When the action priority determiner 125 is not allowed to bring theparameter value from the dialogue and action state DB 147, the contextinformation DB 142, the long-term memory 143, or the short-term memory144, the action priority determiner 125 may request the parameter valueto the external information manager 126.

For example, the destination distance may be brought from the externalcontent server 300 providing a navigation service, and DTE may bebrought from the context information DB 142 via the external informationmanager 126. Meanwhile, in order to search for the destination distance,correct destination information used for the navigation service may beneeded. In the embodiment, a destination which is input from the user'sutterance may correspond to “seoul station”, wherein “seoul station” mayinclude a variety of places having a name started with “seoul station”,and “Seoul station” having a particular meaning. Therefore, it may bedifficult to search for a correct destination distance by using only“seoul station”

As needed, it may be possible to bring the parameter value from themobile device 400 connected to the vehicle 200. For example, when userinformation, e.g., contacts, and schedule which are not stored in thelong-term memory 143, is needed as the parameter value, the externalinformation manager 126 may request the needed information to the mobiledevice 400 and then acquire the needed parameter value.

When it may be impossible to acquire the parameter value via the storage140, the external content server 300 and the mobile device 400, it maybe possible to acquire the needed parameter value by asking the user.

The action priority determiner 125 may determine the execution conditionof the candidate action by using the parameter value. Since thedestination distance is not searched, the determination of the executioncondition related to the vehicle state check action and the gasolinestation recommendation may be postponed.

As illustrated in FIG. 34, the dialogue action manager 122 may updatethe action state by adding the acquired parameter value and whether tomeet the action execution condition, which is determined by using thecorresponding parameter value, to the dialogue and action state DB 147.

The dialogue action manager 122 may request the parameter list used toexecute the candidate actions, to the parameter manager 124.

The parameter manager 124 may extract the current position anddestination as the necessary parameter used for the execution of theroute guidance action, from the action parameter DB 146 a and extractthe route type (initial value: fast route) as the alternative parameter.

The parameter manager 124 may extract check part (initial value: entirepart) used for the execution of the vehicle state check action, as thealternative parameter, and extract the favorite gasoline station(initial value: A-oil) as the alternative parameter used for theexecution of the gasoline station recommendation action.

The extracted parameter list may be transmitted to the dialogue actionmanager 122 and used for updating the action state.

The parameter manager 124 may search for the corresponding parametervalue in the reference position of each parameter in the dialogue andaction state DB 147, the context information DB 142, the long-termmemory 143 and the short-term memory 144 to acquire a parameter valuecorresponding to the necessary parameter and the alternative parameterof the candidate actions. When it is needed that the parameter value isprovided via the external service, the parameter manager 124 may requestthe needed parameter value to the external content server 300 via theexternal information manager 126.

The parameter used to determine the execution condition of the candidateaction and the parameter used to execute the candidate action may beduplicated. When there is a parameter corresponding to a parameter(necessary parameter and alternative parameter) used to execute thecandidate actions, among the parameter values, which is acquired by theaction priority determiner 125 and then stored in the dialogue andaction state DB 147, the corresponding parameter may be used.

Referring to FIG. 35, the dialogue action manager 122 may update theaction state by adding the parameter value acquired by the parametermanager 124.

As mentioned above, when using a destination (seoul station) extractedfrom the user's utterance as the parameter of the route guidance action,there may be the ambiguity. Therefore, a parameter of the route guidanceaction (destination), a parameter of the vehicle state check action(destination distance), and a parameter of the gasoline stationrecommendation (destination distance) may be not yet acquired.

The ambiguity solver 123 may check whether there is the ambiguity when[parameter: NLU: destination: seoul station] is converted into adestination parameter appropriate for the route guidance action. Asmentioned above, “seoul station” may include different kind of placeshaving a name started with “seoul station”, and “Seoul station” having aparticular meaning by a user.

The ambiguity solver 123 may confirm that there is a modifier for “seoulstation” among the user utterance, by referring to the morphologicalanalysis result. The ambiguity solver 123 may search for the schedule,the moving position and the contact, in the long-term memory 143 or theshort-term memory 144 to identify the location of “seoul station we wentyesterday”

For example, the ambiguity solver 123 may confirm that “seoul station wewent yesterday” is “Seoul station exit 4”, from the user's movingposition performed yesterday. After confirming that POI, e.g., “Seoulstation exit 4” is present, the ambiguity solver 123 may bring thecorresponding value.

The destination information acquired by the ambiguity solver 123 may betransmitted to the dialogue action manager 122 and the dialogue actionmanager 122 may update the action state by adding “Seoul station exit 4”to the destination parameter of the candidate action.

The parameter manager 124 may bring the destination information (Seoulstation exit 4) from the dialogue and action state DB 147 and request adestination distance value to the external content server 300 providingthe navigation service via the external information manager 126.

Referring to FIG. 36, when the external information manager 126 acquiresthe destination distance value (80 km) from the external content server300 and then transmit the destination distance value to the parametermanager 124, the parameter manager 124 may transmit the destinationdistance value to the dialogue action manager 122 to allow the actionstate to be updated.

The action priority determiner 125 may determine whether the candidateactions is executable by referring to the action state, and adjust thepriority of the candidate actions. It may be determined that the routeguidance action is executable since the parameter value of the currentposition and destination which are the necessary parameter are acquired.It may be determined that the vehicle state check action is notexecutable since the destination distance (70 km) is less than 100 km.It may be determined that the gasoline station recommendation action isexecutable since the destination distance (80 km) is greater than DTE.

Since the vehicle state check action is not executable, the vehiclestate check action may be excluded from the determination of thepriority. Therefore, the route guidance action may be ranked as thefirst and the gasoline station recommendation action may be ranked asthe second.

The dialogue action manager 122 may update the action state according towhether the candidate action is executable or not, and the modifiedpriority.

The dialogue flow manager 121 may check the dialogue state and theaction state stored in the dialogue and action state DB 147 and maydevelop a dialogue strategy to continue the dialogue by referring to thedialogue policy DB 148. For example, the dialogue flow manager 121 mayselect the highest priority action among the executable actions, and thedialogue flow manager 121 may request that the response generationmanager 131 generate a response for the progress of the dialogueaccording to the dialogue policy DB 148.

The dialogue state and the action state stored in the dialogue andaction state DB 147 may be updated to [state: confirm route guidancestart]

Referring to FIG. 37, the response generation manager 131 may requestthe generation of the response to the dialogue response generator 132 inresponse to the request of the dialogue flow manager 121.

The dialogue response generator 132 may generate a TTS response and atext response by searching the response template 149. For example, thedialogue response generator 132 may generate a dialogue responseconfigured to output “It is expected to take 30 minutes from Uiwangstation to Seoul station Exit 4. Do you want to start the guidance?” asTTS and text form.

The response generation manager 131 may transmit TTS response and textresponse generated by the dialogue response generator 132 to the outputmanager 133 and the memory manager 135, and the output manager 133 maytransmit the TTS response to the speaker 232 and transmit the textresponse to the display 231. In this time, the output manager 133 maytransmit the TTS response to the speaker 232 after passing thorough theTTS module configured to combine the text to the speech.

The memory manager 135 may store that a user requests the routeguidance, in the short-term memory 144 or the long-term memory 143.

The dialogue response configured to ask “It is expected to take 30minutes from Uiwang station to Seoul station Exit 4. Do you want tostart the guidance?” may be output via the display 231 and the speaker232. As illustrated in FIG. 38, when a user utters “yes”, the user'sutterance may be input to the speech recognizer 111 a and then output as[text: yes] and the natural language understanding portion 111 b mayoutput [domain:-], [action:-], [speech act:-], and [morphologicalanalysis result: yes/IC]

The natural language understanding result may be transmitted to thedialogue input manager 111 c and the dialogue input manager 111 c maytransmit the natural language understanding result to the dialoguemanager 120.

Referring to FIG. 39, the dialogue flow manager 121 may search thedialogue and action state DB 147 and analyze the previous dialoguestate. The dialogue flow manager 121 may request that the dialogueaction manager 122 update dialogue/action related to [route guidance]that is currently executed.

The dialogue action manager 122 may update the dialogue state and theaction state to [state: route guidance start].

The dialogue flow manager 121 may request that the result processor 130generate a response for starting the route guidance.

Referring to FIG. 40, the dialogue action manager 122 may update thedialogue state to [state: next dialogue progress] and update the actionstate to [state: execute].

The dialogue flow manager 121 may request that the response generationmanager 131 generate a response for the route guidance.

The dialogue response generator 132 may generate a dialogue responseconfigured to output “start route guidance” as TTS and text form, andthen transmit the dialogue response to the response generation manager131.

The command generator 136 may generate a command for executing the routeguidance [target: navigation, command: route guidance, destination:Seoul station exit 4, departure: Uiwang station], and then transmit thecommand to the response generation manager 131.

The response generation manager 131 may transmit the generated dialogueresponse and command to the output manager 133. The output manager 133may output the dialogue response via the display 231 and the speaker232. The output manager 133 may transmit the route guidance command tothe AVN 230 of the vehicle 200 via the vehicle controller 240 or to theexternal content server 300 providing the navigation service.

Referring to FIG. 41, the dialogue flow manager 121 may select thegasoline station recommendation as the next executable action, andrequest that the response generation manager 131 generate a response,which is configured to ask a user whether to recommend the gasolinestation.

The dialogue state and the action state may be updated to [state: checkrelated service recommendation].

The response generation manager 131 may request that the dialogueresponse generator 132 generate a TTS response and a text response, andthe dialogue response generator 132 may generate a dialogue responseconfigured to output “there is not enough fuel to reach the destination.Do you want to add A-oil station to the stopover?” in the TTS and textform. The dialogue response generator 132 may transmit the TTS and textto the response generation manager 131.

The response generation manager 131 may transmit the TTS response andtext response generated by the dialogue response generator 132 to theoutput manager 133 and the memory manager 135, and the output manager133 may transmit the TTS response to the speaker 232 and transmit thetext response to the display 231.

The dialogue response configured to ask “there is not enough fuel toreach the destination. Do you want to add A oil station to thestopover?” may be output via the display 231 and the speaker 232. Asillustrated in FIG. 42, when a user utters “no”, the user's utterancemay be input to the speech recognizer 111 a and then output as [text:no] and the natural language understanding portion 111 b may output[domain:-], [action:-], [speech act:-], and [morphological analysisresult: no/IC]

The dialogue flow manager 121 may request the dialogue action manager122 update the dialogue state and the action state.

The dialogue action manager 122 may update the dialogue state to [state:next dialogue progress] and update the action state to [state: CANCEL].

The dialogue flow manager 121 may request that the response generationmanager 131 generate a response indicating that the gasoline stationrecommendation service is cancelled, and the dialogue flow manager 121may check whether a dialogue to be sequentially continued, is present.When the dialogue to be sequentially continued, is not present, thedialogue flow manager 121 may update the dialogue state to [state: IDLE]and wait for the user's input.

The above mentioned flow of the data processing is merely an exampleapplied to the dialogue system 100. Therefore, the order of processingdata by each component of the dialogue system 100 is not limited to theabove mentioned example, and thus the plurality of components mayprocess the data at the same time or the plurality of components mayprocess the data in an order that is different from the above mentionedexample.

Hereinafter according to an embodiment, a dialogue processing methodwill be described. According to an embodiment, the dialogue processingmethod may be applied to the above mentioned dialogue system 100 or thevehicle 200 provided with the dialogue system 100. Therefore, thedescription of FIGS. 1 to 42 will be applied to the dialogue processingmethod in the same manner.

FIG. 43 is a flowchart illustrating a method of processing a user'sinput in a dialogue processing method in accordance with an embodiment.The method of processing the user's input may be performed in the inputprocessor 110 of the dialogue system 100.

Referring to FIG. 43, when a user's utterance is input (YES in 500), thespeech recognizer 111 a may recognize the input user's utterance (510).The user's utterance may be input to the speech input device 210provided in the vehicle 200 or the speech input device 410 provided inthe mobile device 400.

The speech recognizer 111 a may recognize the input user's utterance andoutput an utterance in the text form.

The natural language understanding portion 111 b may apply the naturallanguage understanding technology to the utterance in the text form,(520) and output a result of the natural language understanding.

Particularly, the natural language understanding process (520) mayinclude performing morphological analysis on the utterance in the formof text (521), extracting a domain from the utterance based on themorphological analysis result (522), recognizing an entity name (523),analyzing a speech act (524) and extracting an action (525).

The extraction of the domain, the recognition of the entity name and theextraction of the action may be performed by referring to thedomain/action inference rule DB 141.

The output of the natural language understanding portion 111 b, i.e.,the result of the natural language understanding, may include a domain,an action, a speech act, and a result of the morphological analysiscorresponding to the user's utterance.

The context information related to the extracted action may be searched(530). The context information related to the extracted action may bestored in the context understating table 145. The context understandingportion 112 c may search for the context information related to theextracted action, in the context understating table 145 and the contextinformation processor 112 may bring the information value of thesearched context information from the context information DB 142, thelong-term memory 143 or the short-term memory 144.

When additional context information is needed (YES in 540), that is acase in which context information is not acquired from the contextinformation DB 142, the long-term memory 143 or the short-term memory144, the context understanding portion 112 c may request the collectionof the corresponding context information (550). The input except for thespeech, e.g., the vehicle state information, the surrounding environmentinformation, and the driver information may be input via the contextinformation collector 112 a, which is performed separately from theinput of the user's utterance.

The information may be periodically input or input only when a certainevent occurs. In addition, the information may be periodically input andthen additionally input when a certain event occurs. In any cases, whenthe collection of the information is requested, the correspondinginformation may be actively collected.

Therefore, when the context information related to the action is alreadycollected, the corresponding information may be brought from the contextinformation DB 142, the long-term memory 143 or the short-term memory144 or otherwise, the corresponding information may be collected via thecontext information collector 112 a.

When the context information collector 112 a receiving the request forcollecting the context information collects the corresponding contextinformation and stores the information in the context information DB142, the context understanding portion 112 c may bring the correspondingcontext information from the context information DB 142.

When the context information collection manager 112 b determines that acertain event occurs since data collected by the context informationcollector 112 a satisfies a predetermined condition, the contextinformation collection manager 112 b may transmit an action triggersignal to the context understanding portion 112 c.

The context understanding portion 112 c may search the contextunderstating table 145 for searching for context information related tothe corresponding event, and when the searched context information isnot stored in the context understating table 145, the contextunderstanding portion 112 c may transmit a context information requestsignal to the context information collection manager 112 b, again.

When the collection of the needed context information is completed, theresult of the natural language understanding and the context informationmay be transmitted to the dialogue manager 120 (560). When the eventoccurs, information related to the event (which event occurs) and thecontext information related to the occurred event may be alsotransmitted.

FIG. 44 is a flowchart illustrating a method of managing the dialogueusing the output of the input processor in the dialogue processingmethod in accordance with an embodiment. The dialogue processing methodmay be performed by the dialogue manager 120 of the dialogue system 100.

Referring to FIG. 44, the dialogue flow manager 121 may search for therelated dialogue history in the dialogue and action state DB 147 (600).

In the embodiment, the case in which the domain and action is extractedfrom the user's utterance has been described as an example, but theremay be a case in which it is impossible to extract a domain and anaction from the user's utterance, since there is the ambiguity in theutterance content or the context. In this case, the dialogue actionmanager 122 may generate a random dialogue state and the ambiguitysolver 123 may identify the user's intention based on the content of theuser's utterance, the environment condition, the vehicle state, and theuser information, and determine an action appropriate for the user'sintention.

When the related dialogue history is present (YES in 600), the relateddialogue history may be referred (690). When the related dialoguehistory is not present (NO in 600), new dialogue task and action taskmay be generated (610).

A related action list, which is related to the action extracted from theuser's utterance (hereinafter refer to input action), may be searched inthe relational action DB 146 b and candidate actions list may begenerated (620). The input action and actions related to the inputaction may correspond to the candidate actions list.

The execution condition according to each candidate action may besearched in the action execution condition DB 146 c (620). The executioncondition may represent a necessary condition for the execution of theaction. Therefore, when the corresponding condition is met, it may bedetermined that the action is executable but when the correspondingcondition is not met, it may be determined that the action is notexecutable. In the action execution condition DB 146 c, informationrelated to the type of the parameter used for determining the actionexecution condition may be also stored.

The parameter value used for determining the action execution conditionmay be acquired (640). The parameter used for determining the actionexecution condition may be referred to as the condition determinationparameter. The parameter value of the condition determination parametermay be acquired by searching the context information DB 142, thelong-term memory 143, the short-term memory 144 or the dialogue andaction state DB 147. When it is needed that the parameter value of thecondition determination parameter is provided via the external service,the needed parameter value may be provided from the external contentserver 300 via the external information manager 126.

When it is impossible to acquire the needed parameter value due to theambiguity in the context and the utterance, the needed parameter valuemay be acquired by resolving the ambiguity using the ambiguity solver123.

Although the acquired parameter is an ineffective parameter havingdifficulties in the action execution condition determination, theambiguity solver 123 may acquire the effective parameter from theineffective parameter.

Based on the acquired condition determination parameter, whether eachcandidate action is executable may be determined (650), and the priorityof the candidate actions may be determined (660). The rule fordetermining the priority of the candidate actions may be pre-stored. Theaction priority determiner 125 may determine the priority of thecandidate actions by considering only the executable candidate actionsafter determining whether each candidate action is executable.Alternatively, after determining the priority of the candidate actionsregardless whether each candidate action is executable, it may bepossible to modify the priority of the candidate actions based onwhether each candidate action is executable.

The parameter list used for executing the candidate actions may besearched in the action parameter DB 146 a (670). The parameter used forexecuting the candidate actions may correspond to the action parameter.The action parameter may include a necessary parameter and analternative parameter.

The parameter value used for executing the candidate actions may beacquired (680). The parameter value of the action parameter may beacquired by searching the context information DB 142, the long-termmemory 143, the short-term memory 144 or the dialogue and action stateDB 147. When it is needed that the parameter value of the actionparameter is provided via the external service, the needed parametervalue may be provided from the external content server 300 via theexternal information manager 126.

When it is impossible to acquire the needed parameter value due to theambiguity in the context and the utterance, the needed parameter valuemay be acquired by resolving the ambiguity using the ambiguity solver123.

Although the acquired parameter is an ineffective parameter havingdifficulties in the action execution condition determination, theambiguity solver 123 may acquire the effective parameter from theineffective parameter.

The dialogue state and the action state managed by the dialogue actionmanager 122 may be performed by the above mentioned steps and thedialogue state and the action state may be updated whenever the state ischanged.

When all of the obtainable parameter values are obtained, the dialogueflow manager 121 may transmit information related to the candidateactions and the dialogue state, to the result processor 130. Accordingto the dialogue policy, the dialogue flow manager 121 may transmit theinformation related to the action corresponding to the first priority orinformation related to the plurality of the candidate actions.

When the needed parameter value is acquired through only the user sincethe needed parameter value is not present in the external content server300, the long-term memory 143, the short-term memory 144 and the contextinformation DB 142, it may be possible to output a dialogue response forasking parameter values to a user.

FIG. 45 is a flowchart illustrating a result processing method forgenerating a response corresponding to a result of the dialoguemanagement in the dialogue processing method in accordance with anembodiment. The result processing method may be performed by the resultprocessor 130 of the dialogue system 100.

Referring to FIG. 45, when the generation of the dialogue response isneeded (YES in 700), the dialogue response generator 132 may search theresponse template 149 (710). The dialogue response generator 132 mayextract a dialogue response template corresponding to the currentdialogue state and action state, and fill the response template with theneeded parameter value so as to generate the dialogue response (720).

When the parameter value needed for the generation of the dialogueresponse is not transmitted from the dialogue manager 120, or when anintroduction of using the external content, is transmitted, the neededparameter value may be provided from the external content server 300 orsearched in the long-term memory 143, the short-term memory 144 or thecontext information DB 142. When the needed parameter value is acquiredthrough only the user since the needed parameter value is not present inthe external content server 300, the long-term memory 143, theshort-term memory 144 and the context information DB 142, it may bepossible to generate a dialogue response for asking parameter values tothe user.

When the generation of the command is needed (760), the commandgenerator 136 may generate the command for the vehicle control or theexternal content (770).

The generated dialogue response or command may be input to the outputmanager 133 and the output manager 133 may determine the output orderbetween the dialogue response and the command or the output order amongthe plurality of the commands (730).

The memory may be updated based on the generated dialogue response orcommand (740). The memory manager 135 may update the short-term memory144 by storing the dialogue content between the user and the systembased on the generated dialogue response or command, and update thelong-term memory 143 by storing the information related to the useracquired through the dialogue with the user. The memory manager 135 mayupdate the user's preference and the vehicle control history stored inthe long-term memory 143 based on the generated and output vehiclecontrol and external content request.

The output manager 133 may output the response by transmitting thedialogue response and command to an appropriate output position (750).TTS response may be output via the speaker 232 and text response may beoutput on the display 231. The command may be transmitted to the vehiclecontroller 240 according to the control target, or to the externalcontent server 300. In addition, the command may be transmitted to thecommunication device 280 configured to communicate with the externalcontent server 300.

FIGS. 46 to 48 is a flowchart illustrating a case in which the dialoguesystem outputs a pre-utterance before a user inputs an utterance in thedialogue processing method in accordance with an embodiment.

Referring to FIG. 46, the context information collector 112 a and thecontext information collection manager 112 b collect the contextinformation (810). Particularly, the vehicle controller 240 may inputinformation acquired by the sensor provided in the vehicle, e.g., aremaining amount of fuel, an amount of rain, a rain speed, surroundingobstacle information, a speed, an engine temperature, a tire pressure,current position, and driving environment information, to the contextinformation processor 112. The user information input via theinformation except for speech input device 220 and information acquiredfrom the external content server 300 or the external device may be inputto the context information processor 112. The collected contextinformation may be stored in the context information DB 142, thelong-term memory 143, or the short-term memory 144.

The pre-utterance determiner 151 determines the pre-utterance conditionbased on the context information (811). The pre-utterance condition maybe stored in the pre-utterance condition table 145 a. As illustrated inFIGS. 22A to 22C, the pre-utterance condition related to the contextinformation may be stored for each context information in thepre-utterance condition table 145 a.

When the context information transmitted from the context information DB142, the long-term memory 143, or the short-term memory 144 satisfiesthe pre-utterance condition (YES in 812), the pre-utterance determiner151 determines that it is the pre-utterance context, and generates thepre-utterance trigger signal (813).

The pre-utterance determiner 151 extracts an action corresponding to thepre-utterance context (814). As illustrated in FIG. 22C, an actioncorresponding to the pre-utterance context may be pre-stored in thepre-utterance condition table 145 a. The pre-utterance determiner 151may extract an action corresponding to the pre-utterance context, fromthe pre-utterance condition table 145 a. In addition, the pre-utterancedeterminer 151 may generate an action corresponding to the pre-utterancecontext, according to the established rules.

When the pre-utterance determiner 151 transmits the pre-utterancetrigger signal with the action corresponding to the pre-utterancecontext, to the dialogue input manager 111 c, the dialogue input manager111 c transmits the action corresponding to the pre-utterance context,to the dialogue manager 120 (815). In this case, it may be possible totransmit the pre-utterance trigger signal with a signal indicating thepre-utterance context.

After the action corresponding to the pre-utterance context istransmitted to the dialogue manager 120, a series of process, such asthe generation of the dialogue task and the action task, and theacquirement of the action parameter, may be performed as illustrated inFIG. 44. When other dialogue task or action task is performed, thedialogue flow manager 121 may firstly generate and process the taskrelated to pre-utterance context or may select the priority according tothe established rules.

When the dialogue manager 120 transmits information related to theaction that is firstly performed, to the result processor 130, thedialogue response generator 132 may extract a dialogue response templateby searching the response template 149, and generate the dialogueresponse by filling the extracted dialogue response template with theparameter value. The generated dialogue response may be transmitted tothe output manager 133 via the response generation manager 131. Theoutput manager 133 may output the generated dialogue response via thespeaker provided in the vehicle 200 or the mobile device 400.

Further, it may be possible to obtain or generate the pre-utterancemessage as it is, corresponding to the pre-utterance context. Referringto FIG. 47, the context information collector 112 a and the contextinformation collection manager 112 b collect the context information(820) and the pre-utterance determiner 151 determines the pre-utterancecondition based on the context information (821).

When the context information transmitted from the context information DB142, the long-term memory 143, or the short-term memory 144 satisfiesthe pre-utterance condition (YES in 822), the pre-utterance determiner151 determines that it is the pre-utterance context, and generates thepre-utterance trigger signal (823).

The pre-utterance determiner 151 extracts a pre-utterance messagecorresponding to the pre-utterance context (824). As illustrated inFIGS. 22A and 22B, a pre-utterance message corresponding to thepre-utterance context may be pre-stored in the pre-utterance conditiontable 145 a. The pre-utterance message stored in advance may be acontent indicating the current context or a content which firstlysuggests the execution of the certain function or the service needed forthe pre-utterance context. In addition, the pre-utterance determiner 151may generate a pre-utterance message according to the established rules.

When the pre-utterance determiner 151 transmits the pre-utterancetrigger signal with the pre-utterance message, to the dialogue inputmanager 111 c, the dialogue input manager 111 c may transmit thepre-utterance message, to the dialogue manager 120 (825). In this case,it may be possible to transmit the pre-utterance trigger signal with asignal indicating the pre-utterance context.

The dialogue manager 120 may generate the dialogue task for outputtingthe transmitted pre-utterance message, and transmit the dialogue task tothe result processor 130. The result processor 130 may output the inputpre-utterance message, via the speaker 232.

Further, it may be possible to extract a virtual user utterancecorresponding to the pre-utterance context. Referring to FIG. 48, thecontext information collector 112 a and the context informationcollection manager 112 b collect the context information (830) and thepre-utterance determiner 151 determines the pre-utterance conditionbased on the context information (831).

When the context information transmitted from the context information DB142, the long-term memory 143, or the short-term memory 144 satisfiesthe pre-utterance condition (YES in 832), the pre-utterance determiner151 determines that it is the pre-utterance context, and generates thepre-utterance trigger signal (833).

The pre-utterance determiner 151 extracts a virtual user utterancecorresponding to the pre-utterance context (834). Although not shown inthe drawings, a virtual user utterance corresponding to thepre-utterance context may be pre-stored in the pre-utterance conditiontable 145 a. The pre-utterance determiner 151 may extract the virtualuser utterance corresponding to the pre-utterance context from thepre-utterance condition table 145 a. In addition, the pre-utterancedeterminer 151 may generate a virtual user utterance corresponding tothe pre-utterance context, according to the established rules.

When the pre-utterance determiner 151 transmits the virtual userutterance in the text form, to the natural language understandingportion 111 b (835), the natural language understanding portion 111 bmay extract a domain and action from the virtual user utterance, in thesame manner as a case in which the user actually utters.

The dialogue input manager 111 c transmits the pre-utterance triggersignal with the result of natural language understanding, to thedialogue manager 120 (836). The result of natural language understandingmay include a domain and action extracted from the virtual userutterance, and the extracted domain and action may become a domain andaction corresponding to the pre-utterance context.

For example, according to the mobile gateway method in which the mobiledevice 400 acts as a gateway between the vehicle and the dialogue system100, the dialogue system client 470 of the mobile device 400 may performsome of operations of the pre-utterance determiner 151. In this case,the dialogue system client 470 may generate the virtual user utterancecorresponding to the pre-utterance context and transmit the virtual userutterance to the natural language understanding portion 111 b.

After the pre-utterance trigger signal with the result of naturallanguage understanding are transmitted to the dialogue manager 120, aseries of process, such as the generation of the dialogue task and theaction task, and the acquirement of the action parameter, may beperformed as illustrated in FIG. 44. When other dialogue task or actiontask is performed, the dialogue flow manager 121 may firstly generateand process the task related to pre-utterance context or may select thepriority according to the established rules.

When the dialogue manager 120 transmits information related to theaction that is firstly performed, to the result processor 130, thedialogue response generator 132 may extract a dialogue response templateby searching the response template 149, and generate the dialogueresponse by filling the extracted dialogue response template with theparameter value. The generated dialogue response may be transmitted tothe output manager 133 via the response generation manager 131. Theoutput manager 133 may output the generated dialogue response via thespeaker provided in the vehicle 200 or the mobile device 400.

FIG. 49 is a flowchart illustrating of processing a duplicate task whenthe dialogue system outputs a pre-utterance before a user inputs anutterance in the dialogue processing method in accordance with anembodiment.

Referring to FIG. 49, the context information collector 112 a and thecontext information collection manager 112 b collect the contextinformation (840) and the pre-utterance determiner 151 determines thepre-utterance condition based on the context information (841).

The pre-utterance determiner 151 determines whether the contextinformation transmitted from the context information DB 142, thelong-term memory 143, or the short-term memory satisfies thepre-utterance condition, and when the context information satisfies thepre-utterance condition (YES in 842), the duplicate task processor 152determines whether a task related to the pre-utterance context thatcurrently occurs, is duplicate or not (843).

Particularly, the duplicate task processor 152 may determine whether atask, such as a dialogue and an action related to the pre-utterancecontext that currently occurs, is already performed or is currentlyperformed, based on the information, which is related to a task that ispreviously or currently performed in the dialogue system 100, stored inthe task processing DB 145 b.

For example, when a dialogue related to the pre-utterance context thatcurrently occurs is already performed, and when a reference period oftime is not elapsed from the dialogue point of time, the duplicate taskprocessor 152 may determine that the task related to the currentpre-utterance context is a duplicate task. In addition, when thedialogue and action related to the current pre-utterance context iscurrently performed, the duplicate task processor 152 may determine thatthe task related to the current pre-utterance context is a duplicatetask.

That is, the duplicate task processor 152 may determine whether thepre-utterance is already output or not and the user's intention aboutthe pre-utterance context, based on the dialogue history and whether thetask is performed or not, which are stored in the task processing DB 145b. The duplicate task processor 152 may determine whether it is aduplicate task or not, based on the stored dialogue time, the user'sintention or whether the task is processed or not.

When it is identified that the task related to the current pre-utterancecontext is a duplicate task (YES in 843), the duplicate task processor152 terminates the pre-utterance context.

When it is determined that the task related to the current pre-utterancecontext is not a duplicate task (NO in 843), it may be possible toperform the pre-utterance operation as illustrated in theabove-mentioned embodiment (844). For example, it may be possible totransmit the pre-utterance trigger signal and the action or thepre-utterance message corresponding to the pre-utterance context, to thedialogue manager 120. In addition, it may be possible to transmit thevirtual user utterance corresponding to the pre-utterance context, tothe natural language understanding portion 111 b, and transmit theresult of natural language understanding and the pre-utterance triggersignal, to the dialogue manager 120.

According to the above-mentioned embodiment, it is assumed thatadditional components, such as the pre-utterance determiner 151, and theduplicate task processor 152 and additional storage, such as thepre-utterance condition table 145 a and the task processing DB 145 b areused to perform the dialogue processing method for the pre-utterance.However, embodiments of the dialogue processing method are not limitedthereto, but the context understanding portion 112 c may perform theoperation of the pre-utterance determiner 151 and the duplicate taskprocessor 152 and the information stored in the pre-utterance conditiontable 145 a and the task processing DB 145 b may be stored in thecontext understating table 145.

The dialogue processing method according to an embodiment is not limitedthe order in the above mentioned flowchart. The flow according to theflowchart of FIGS. 41 to 49 may be merely an example applied to thedialogue processing method. Therefore, the plurality of steps may beperformed at the same time it may be also possible to change the orderof each step.

FIG. 50 is a control block diagram illustrating a vehicle gateway methodin which a dialogue system is provided in a remote server and a vehicleacts as a gateway connecting a user to the dialogue system.

Hereinafter, a detailed description of the same configuration asdescribed in the above description of FIG. 11 will be omitted.

Further, a description thereof will be described with reference to FIGS.51 to 53 illustrating a method for acquiring user labeling contextinformation.

According to the vehicle gateway method, as illustrated in FIG. 50, aremote dialogue system server 1 may be provided in the outside of thevehicle 200, and a dialogue system client 270 connected via the remotedialogue system server 1 and the communication device 280 may beprovided in the vehicle 200. The communication device 280 serves as agateway for connecting the vehicle 200 and the remote dialogue systemserver 1.

The dialogue system client 270 may serve as an interface connected to aninput/output device and perform collecting, and sending and receivingdata.

When the speech input device 210 and the information except for speechinput device 220 provided in the vehicle 200 receive a user's input andtransmit the user input to the dialogue system client 270, the dialoguesystem client 270 may transmit the input data to the remote dialoguesystem server 1 via the communication device 280.

The vehicle controller 240 may also transmit data detected by thevehicle detector 260 to the dialogue system client 270 and the dialoguesystem client 270 may transmit the data detected by the vehicle detector260 to the remote dialogue system server 1 via the communication device280.

According to a response transmitted from the remote dialogue systemserver 1, the vehicle 200 may bring information or content for theservice needed for the user from the external content server 300.

The communication device 280 may include at least one communicationmodule configured to communicate with an external device. For example,the communication device 280 may include at least one of the short rangecommunication module 281, the wired communication module 282, and thewireless communication module 283.

Since the above mentioned dialogue system 100 is provided in the remotedialogue system server 1, the remote dialogue system server 1 mayperform all of input data processing, dialogue processing based on theresult of the input data processing, and result processing based on theresult of the dialogue processing.

In addition, the remote dialogue system server 1 may bring informationor content needed for the input data processing, the dialoguemanagement, or the result processing, from the external content server300.

Particularly, the dialogue system 100 may include the input processor110, the dialogue manager 120, the result processor 130, and the storage140.

The input processor 110 may recognize a user's speech, which istransmitted when the user performs an utterance, as a text, and assign aweight to the text according to objective context information at thetime when the user's speech is recognized. The input processor 110 mayidentify an entity of the text and then acquire user labeling contextinformation. When user's free utterance or designated entity utteranceoccurs, the input processor 110 may acquire at least one of an actioncorresponding to the user's free utterance or the designated entityutterance, and a pre-utterance message having an utterance content to beoutput.

The user labeling is defined as search indexing information foracquiring context information based on a user's utterance. In addition,the user labeling context information is defined as defining contextinformation that is searched based on the user labeling.

When a button (push-to-talk) provided on the inside or the outside ofthe vehicle for the user utterance is selected by the user or when atleast one of a predetermined speech (e.g., a pre-determined call word)or gesture is performed by the user, a trigger signal is generated.Therefore, the user's utterance may be recorded and then transmitted tothe input processor 110, through the speech input device provided on theinside or the outside of the vehicle.

The input processor 110 may perform morphological analysis on the user'sspeech according to the language and convert the user's speech into atext. At this time, the morphological analysis is optional, and it isalso possible to perform the text conversion without the morphologicalanalysis.

The input processor 110 may correct the text using unique named entityrecognition when a place, a name, music, and a movie and a pre-storedunique named entity are stored in the storage 140. When performing theentity recognition, it may be possible to correct some of the text notthe unique named entity.

The input processor 110 may call objective context information includingat least one of time information, place information, schedule, user'sposition in inside or outside of the vehicle or driving information fromthe storage 140 and assign a weight according to the importance andspecificity of the objective context information.

For example, the time information may include daily timeline, day of theweek, a specific holiday, and a season, and the place information mayinclude a nearby POI, a place stored between house and company, and aroad type, and the driving information may include speed, gears, andacceleration.

At this time, the input processor 110 may also acquire objective contextinformation from the outside including the external content server 300,in addition to the storage 140.

The input processor 110 may assign a weight to frequency of referencingof an associative entity and the objective context information accordingto time, place, driving and boarding state, and vehicle drivinginformation.

For example, when the vehicle drives and the user boards on the vehicle,the input processor 110 may firstly search for a vehicle, a schedule, aposition of interest (POI), and a time-related entity and assign aweight thereto. In addition, when the daily timeline is night, holidayor weekends, the input processor 110 may firstly search for an entityrelated to schedule, leisure time, contact information, and POI, andassign a weight thereto. In addition, when a place is a road during thevehicle drives, the input processor 110 may firstly search for an entityrelated to the road such as a rest stop, an entrance and exit and a fee.

The input processor 110 may search for an entity having a weight inorder of the weight having the higher priority and derive user labelingcontext information by using a word that describes the property of theentity, as a label and then transmit the user labeling contextinformation to the storage 140 for constituting the ontology.

Particularly, the input processor 110 may first verify an entity havinga high weight, search for a word describing a property of the entity,and connect the property description word to the entity. The inputprocessor 110 may firstly search for an entity having a high weightaccording to a weight based on time, place, driving and boarding state,and vehicle driving information and use the word describing the propertyof the entity, as a label so as to acquire user labeling contextinformation and transmit the user labeling context information to thestorage 140 for constituting the ontology.

When the vehicle drives and the user boards on the vehicle, the inputprocessor 110 may firstly search for an entity related to a vehicle, aschedule, POI, and time and assign a weight to the entity.

Referring to FIG. 51, when the user's utterance is ‘This cafe coffee isdelicious, so it is worth to stop by for a moment’, the input processor110 may call coffee shop information and POI business name from a mapand change an entity name ‘this café ’ into ‘A coffee shop’, assign alabel ‘coffee is delicious, change an entity name ‘for a moment’ into‘within one hour’, and assign a label ‘it is worth to stop by’. “Withinone hour” may be connected to a dependent entity of ‘this café’

The input processor 110 may search for the entity included in pre-storedontology in the storage 140 to derive user labeling context informationby using a word describing the property of the entity as a label, andtransmit the user labeling context information to the storage 140 forconstituting the ontology. At this time, the entity may be in anon-weighted state. The pre-stored ontology may be a public ontology ora specialized ontology in which associative words collections andsimilar meaning is connected for each service function. In other words,it is possible to utilize common sense object information like anencyclopedia as the ontology.

The input processor 110 may derive the user labeling context informationby referring to the pre-stored user information when labeling. At thistime, the user information may include at least one of personalinformation, family, schedule, telephone number, preference,personality, educational history, occupation, current position, previousposition or previous dialogue contents.

Referring to FIG. 52, when the user's utterance is ‘There are far fewerpeople in the gasoline station in the morning’, the input processor 110may call gasoline station information and POI business name from a mapand change an entity name “gasoline station” into “B oil city hallbranch”, assign a label “There are far fewer people”. At this time, theinput processor 110 may verify that there is no association expressionand important information about the entity name ‘morning’, and may set‘morning’ as a dependent entity for ‘gas station’

Referring to FIG. 53, when the user's utterance is ‘It's not easy tostop by kindergarten every morning’, the input processor 110 may callPOI business name about ‘kindergarten’ from a map and change an entityname “kindergarten” into “C kindergarten”, add a label “stop by”, add‘It's not easy’ as a dependent label of ‘stop by’, check a previousdriving record, verify whether a user repeatedly visits thecorresponding place (visit history), check personal information ofuser's child, add an entity ‘son’ that is omitted, and assign the entity‘morning’ as a dependent entity for ‘kindergarten’.

The input processor 110 may verify whether a new route of the vehiclecorresponds to the pre-utterance context identical to the object contextinformation, and when it is determined that it corresponds to thepre-utterance context, the input processor 110 may acquire the entityontology information corresponding to the object context information,from the storage 140, as a pre-utterance message.

The storage 140 may store the user labeling context information derivedby the input processor 110 in such a manner to manage the user labelingcontext information in a form that allows entity ontology to be sharedwith other user.

When storing the user labeling context information, the storage 140 maystore a labeling result and a frequency of referencing ontology entityby searching for the corresponding entity in the pre-stored ontologystructure. In this time, the pre-stored ontology structure may utilizean open source.

According to a user setting, the storage 140 may set and store thelabeling result and the frequency of referencing ontology entity as oneof sharing or non-sharing.

According to a user's request, the storage 140 may allow non-shareddata, shared-data, which is shared with other users, and pre-setontology structure to be browsed.

When the input processor 110 acquires the action corresponding to thefree utterance or the designated entity utterance, the dialogue manager120 may acquire a parameter value of the action parameter that is usedto perform the action corresponding to the free utterance or thedesignated entity utterance, from the storage 140.

When the user performs the free utterance or the designated entityutterance, the dialogue manager 120 may acquire the user labelingcontext information corresponding to the free utterance or thedesignated entity utterance, from the storage 140.

When the input processor 110 acquires an action corresponding to thefree utterance or the designated entity utterance, the result processor130 may generate a dialogue response to perform the action correspondingto the free utterance or the designated entity utterance by using theacquired parameter value of the action parameter.

For example, when a user (e.g., a driver) utters a designated entity‘take a break?’ at a location adjacent to ‘A coffee shop’, the resultprocessor 130 may output a dialogue response such as ‘Would you like togo to near A coffee shop where coffee was delicious?’

In addition, when a user utters ‘Is it time to put gasoline?’ includingan entity or an entity similar word, the result processor 130 may outputa dialogue response such as ‘in the morning, there are far fewer peoplein B oil city hall branch you visited the last time’. In this time‘gasoline’ may be a similar entity of ‘gasoline station’ that is apre-stored entity.

When the input processor 110 acquires the pre-utterance message, theresult processor 130 may generate a dialogue response corresponding tothe transmitted pre-utterance message.

At this time, the input processor 110 may verify whether a new route ofthe vehicle corresponds to a pre-utterance context identical to theobjective context information, and when it is determined that the newroute of the vehicle corresponds to the pre-utterance context, the inputprocessor 110 may acquire entity ontology information corresponding tothe objective context information, as the pre-utterance message, fromthe storage.

For example, when a repeated schedule is detected, the result processor130 may output a pre-utterance message such as ‘it is not easy to stopby C kindergarten in the morning. Would you like to leave 5 minutesearly?’ at the same time every day.

In addition, when the gasoline is not enough and the previously visitedgasoline station is nearby, the result processor 130 may output apre-utterance message ‘fuelling is needed. Would you like to go to thenearby B-oil city hall branch there are few people in this time?’

FIG. 54 is a control block diagram illustrating a vehicle independentmethod in which a dialogue system is provided in a vehicle.

Hereinafter, a detailed description of the same configuration asdescribed in the above description of FIG. 10 will be omitted.

According to the vehicle independent method, the dialogue system 100having the input processor 110, the dialogue manager 120, the resultprocessor 130 and the storage 140 may be contained in the vehicle 200,as illustrated in FIG. 54.

The vehicle 200 may include the speech input device 210 configured toreceive a user's speech and transmit the user's speech, as a triggersignal for the utterance is generated by the user.

When a button provided on the inside or the outside of the vehicle forthe user utterance is selected by the user, or when at least one of apredetermined speech or gesture is performed, a trigger signal may begenerated and thus the speech input device 210 may receive the user'sspeech.

The dialogue system 100 may recognize the user's speech transmitted fromthe speech input device 210, as a text, verifies an entity of the text,derive user labeling context information, store the user labelingcontext information in a state in which entity ontology is shared withother user, and generate a dialogue response to perform an actioncorresponding when the user performs the free utterance or thedesignated entity utterance.

Particularly, the input processor 110 may recognize the user's speech,which is transmitted when a user is uttered, as a text, and assign aweight to the text according to objective context information at thetime when the user's speech is recognized. After verifying an entity ofthe text, the input processor 110 may derive user labeling contextinformation and when the free utterance or designated entity utteranceof the user occurs, the input processor 110 may acquire at least one ofan action, which corresponds to the free utterance or designated entityutterance of the user, and a pre-utterance message including anutterance content to be output.

The input processor 110 may call the objective context informationincluding at least one of the time information, the place information,the schedule, the user's location in the inside or outside of thevehicle or the driving information from the storage 140, and assign aweight to the objective context information according to the importanceand specificity of the objective context information.

The input processor 110 may verify whether a new route of the vehiclecorresponds to the pre-utterance context identical to the object contextinformation, and when it is determined that it corresponds to thepre-utterance context, the input processor 110 may acquire the entityontology information corresponding to the object context information,from the storage 140, as a pre-utterance message.

The storage 140 may store the user labeling context information derivedby the input processor 110 in such a manner to manage the user labelingcontext information in a form that allows entity ontology to be sharedwith other user.

When storing the user labeling context information, the storage 140 maystore a labeling result and a frequency of referencing ontology entityby searching for the corresponding entity in the pre-stored ontologystructure. In this time, the pre-stored ontology structure may utilizean open source.

When the input processor 110 acquires the action corresponding to thefree utterance or the designated entity utterance, the dialogue manager120 may acquire a parameter value of the action parameter that is usedto perform the action corresponding to the free utterance or thedesignated entity utterance, from the storage 140.

When the user performs the free utterance or the designated entityutterance, the dialogue manager 120 may acquire the user labelingcontext information corresponding to the free utterance or thedesignated entity utterance, from the storage 140.

When the input processor 110 acquires an action corresponding to thefree utterance or the designated entity utterance, the result processor130 may generate a dialogue response to perform the action correspondingto the free utterance or the designated entity utterance by using theacquired parameter value of the action parameter.

As is apparent from the above description, according to the proposeddialogue system and vehicle having the same, it may be possible toimprove the user convenience during driving, since the driver isprovided with information that is needed for the driver in the certaincontext, through information, which is uttered by the driver or otherdriver and then labeled.

Although a few embodiments of the present disclosure have been shown anddescribed, it would be appreciated by those skilled in the art thatchanges may be made in these embodiments without departing from theprinciples and spirit of the disclosure, the scope of which is definedin the claims and their equivalents.

According to the proposed dialogue processing apparatus, vehicle havingthe same and dialogue processing method, it may be possible to providethe service that is appropriate for the user's intention or that isneeded for the user by using the dialogue processing method that isspecified for the vehicle.

In addition, it may be possible to provide the service that is needed ofthe user, by considering a variety of contexts that occur in thevehicle. Particularly, regardless the user's utterance, it may bepossible to determine the service that is needed of the user based onthe context information or the driver information collected by thedialogue system 100 and proactively provide the service.

The description of the disclosure is merely exemplary in nature and,thus, variations that do not depart from the substance of the disclosureare intended to be within the scope of the disclosure. Such variationsare not to be regarded as a departure from the spirit and scope of thedisclosure.

DESCRIPTION OF SYMBOLS

-   -   100: dialogue system    -   110: input processor    -   120: dialogue processor    -   130: result processor    -   200: vehicle    -   210: speech input device    -   220: information except for speech input device    -   230: dialogue output device    -   280: communication device

What is claimed is:
 1. A dialogue system comprising: an input processorconfigured to: recognize a user's speech as a text; assign a weight tothe text based on objective context information when the user's speechis recognized; derive user labeling context information after verifyingan entity of the text; and when a free utterance of the user or adesignated entity utterance of the user occurs, acquire at least one ofan action or a pre-utterance message comprising an utterance content tobe output, wherein the action corresponds to the free utterance of theuser or the designated entity utterance of the user; a storageconfigured to: store the user labeling context information; and managethe user labeling context information in a form that allows an entityontology to be shared with other user; a dialogue manager, when theinput processor acquires the action, configured to acquire an actionparameter value that is used to perform the action from the storage; aresult processor, when the input processor acquires the action,configured to generate a dialogue response to perform the action byusing the action parameter value; and a pre-utterance determinerconfigured to: determine a pre-utterance condition based on the userlabeling context information; and generate a pre-utterance triggersignal before the user utters.
 2. The dialogue system of claim 1,wherein the input processor is configured to: perform morphologicalanalysis on the user's speech corresponding to a language; and convertthe user's speech into the text.
 3. The dialogue system of claim 1,wherein the input processor is configured to correct the text using aunique named entity recognition when a pre-stored unique named entityincluding a place, a name, a music, and a movie is stored in thestorage.
 4. The dialogue system of claim 1, wherein the input processoris configured to: call objective context information comprising at leastone of time information, place information, schedule, user's position ininside or outside of the vehicle, or driving information from thestorage; and assign the weight according to an importance and aspecificity of the objective context information.
 5. The dialogue systemof claim 4, wherein the input processor is configured to: search for anentity having a higher weight priority; derive the user labeling contextinformation by using a word that describes a characteristics of theentity as a label; and transmit the user labeling context information tothe storage for constituting ontology.
 6. The dialogue system of claim1, wherein the input processor is configured to: search for the entityincluded in a pre-stored ontology in the storage; derive the userlabeling context information by using the word that describes thecharacteristics of the entity, as the label; and transmit the userlabeling context information to the storage for constituting ontology.7. The dialogue system of claim 6, wherein the input processor isconfigured to derive the user labeling context information by referringto pre-stored user information.
 8. The dialogue system of claim 7,wherein the pre-stored user information comprises at least one ofpersonal information, family, schedule, telephone number, preference,personality, educational history, occupation, current position, previousposition or previous dialogue contents.
 9. The dialogue system of claim1, wherein, when storing the user labeling context information, thestorage is configured to store a labeling result and a frequency ofreferencing the entity ontology by searching for a corresponding entityin a pre-stored ontology structure.
 10. The dialogue system of claim 9,wherein the storage is configured to set and store the labeling resultand the frequency of referencing the entity ontology as one of sharingor non-sharing based on a user setting.
 11. The dialogue system of claim1, wherein, when the free utterance of the user or the designated entityutterance of the user is performed, the dialogue manager is configuredto acquire the user labeling context information corresponding to thefree utterance of the user or the designated entity utterance of theuser from the storage.
 12. The dialogue system of claim 1, wherein theinput processor is configured to: determine whether a new route of avehicle corresponds to a pre-utterance context that is identical to theobjective context information; and when it is determined that the newroute of the vehicle corresponds to the pre-utterance context, acquireentity ontology information corresponding to the objective contextinformation as the pre-utterance message from the storage.
 13. Thedialogue system of claim 1, wherein, when the input processor acquiresthe pre-utterance message, the result processor is configured togenerate a dialogue response corresponding to the pre-utterance message.14. The dialogue system of claim 1, wherein the input processor isconfigured to: receive a user's utterance from a speech input deviceprovided inside or outside of the vehicle when a trigger signal isgenerated or a button for the user's utterance is selected, wherein thetrigger signal is generated when at least one of a predetermined speechor a predetermined gesture is performed by the user.
 15. A vehiclecomprising: a speech input device configured to: receive a user's speechand transmit the user's speech when a trigger signal for an utterance isgenerated by a user; and a dialogue system configured to: recognize theuser's speech as a text; derive user labeling context information afterverifying an entity of the text; store the user labeling contextinformation in a form that allows an entity ontology to be shared withother user; and generate a dialogue response to perform a correspondingaction when the user performs a free utterance or a designated entityutterance; and a pre-utterance determiner configured to: determine apre-utterance condition based on the user labeling context information;and generate a pre-utterance trigger signal before the user utters. 16.The vehicle of claim 15, wherein the speech input device is configuredto: receive the user's speech when the trigger signal is generated or abutton for a user's utterance is selected, wherein the trigger signal isgenerated when at least one of a predetermined speech or a predeterminedgesture is performed by the user.
 17. The vehicle of claim 15, whereinthe dialogue system comprises: an input processor configured to:recognize the user's speech as a text; assign a weight to the text basedon objective context information when the user's speech is recognized;derive user labeling context information after verifying an entity ofthe text; and when a free utterance of the user or a designated entityutterance of the user occurs, acquire at least one of an action or apre-utterance message including an utterance content to be output,wherein the action corresponds to the free utterance of the user or thedesignated entity utterance of the user; a storage configured to: storethe user labeling context information; and manage the user labelingcontext information in a form that allows an entity ontology to beshared with other user; a dialogue manager, when the input processoracquires the action, configured to acquire an action parameter valuethat is used to perform the action from the storage; and a resultprocessor, when the input processor acquires the action, configured togenerate a dialogue response to perform the action by using the actionparameter value.
 18. The vehicle of claim 17, wherein the inputprocessor is configured to: call objective context information includingat least one of time information, place information, schedule, user'sposition in inside or outside of the vehicle, or driving informationfrom the storage; and assign the weight according to an importance and aspecificity of the objective context information.
 19. The vehicle ofclaim 15, wherein, when storing the user labeling context information,the storage is configured to store a labeling result and a frequency ofreferencing the entity ontology by searching for a corresponding entityin a pre-stored ontology structure.
 20. The vehicle of claim 15,wherein, when the free utterance of the user or the designated entityutterance of the user is performed, the dialogue manager is configuredto acquire the user labeling context information corresponding to thefree utterance of the user or the designated entity utterance of theuser from the storage.
 21. The vehicle of claim 15, wherein the inputprocessor is configured to: determine whether a new route of the vehiclecorresponds to a pre-utterance context that is identical to theobjective context information; and when it is determined that the newroute of the vehicle corresponds to the pre-utterance context, acquireentity ontology information corresponding to the objective contextinformation as the pre-utterance message from the storage.